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Preventative health

Primary Care Corner with Geoffrey Modest MD: leisure time activity and lower cancer risk

27 Feb, 17 | by EBM

By Dr. Geoffrey Modest

There have been a plethora of articles in the past year on the beneficial effects of exercise. I will use the next several blogs to sample some of these.

One article looked at the beneficial effects of leisure-time physical activity on 26 cancer types (see doi:10.1001/jamainternmed.2016).


  • 44 million participants from 12 prospective US and European cohorts had self-reported leisure-time physical activity at baseline (1987 to 2004). Leisure-time physical activity levels were assessed as cohort-specific percentiles on a continuous basis. Hazard ratios are based on high vs low activity levels (comparing the 90th versus 10th percentiles of activity)
  • Median age 59 years, 57% females, BMI 26.
  • 186,932 participants with cancer were included in the analysis
  • Moderate activity in general was defined as intensity of >=3 more METS; vigorous activity as >=6 METS (see below for a definition for METS, or Metabolic Equivalents


  • There was a lower risk for 13 cancers with higher levels of leisure-time physical activity (the statistical models controlled for age, sex, smoking, alcohol, race/ethnicity, education; as well as specific risk factors for some cancers, such as hormone therapy, age at menarche, age at menopause, and parity for several of the female-only cancers, etc.):
    • Esophageal adenocarcinoma, decreased 42%, HR 0.58 (0.37-0.89)
    • Liver, decreased 27%, HR 0.73 (0.55-0.98)
    • Lung, decreased 26%, HR 0.74 (0.71-0.77)
    • Kidney, decreased 23%, HR 0.77 (0.70-0.85)
    • Gastric cardia, decreased 22%, HR 0.78 (0.64-0.95)
    • Endometrial, decreased 21%, HR 0.79 (0.68-0.92)
    • Myeloid leukemia, decreased 20%, HR 0.80 (0.70-0.92)
    • Myeloma, decreased 17%, HR 0.83 (0.72-0.95)
    • Colon, decreased 16%, HR 0.84 (0.77-0.91)
    • Head and neck, decreased 15%, HR 0.85 (0.78-0.93)
    • Rectal, decreased 13%, HR 0.87 (0.80-0.95)
    • Bladder, decreased 13%, HR 0.87 (0.82-0.92)
    • Breast, decreased 10%, HR 0.90 (0.87-0.93)
  • But there were higher risks of:
    • Malignant melanoma, increased 27%, HR 1.27 (1.16-1.40)
    • Prostate cancer, increased 5%, HR 1.05 (1.03-1.08): but specifically for non-advanced prostate cancer (HR 1.08), with no association for advanced prostate cancer (HR 0.99)
    • Cancers that did not reach statistical significance included non-Hodgkin’s lymphoma (though this was borderline significant at the P=0.05 level, with an 8% decrease with increased leisure-time activity), thyroid, gastric non-cardia, soft-tissue, pancreas, lymphocytic leukemia, ovary, and brain
    • Controlling for BMI decreased the statistical significance for esophageal carcinoma, and rendered the associations with endometrial cancer, liver and gastric cardia to be nonsignificant
    • Associations were generally similar with overweight/obese versus normal weight individuals
    • Smoking status modified  the association for lung cancer but not the other smoking-related cancers


  • This observational study found the quite impressive result that exercise was associated with major decreases in 13 cancers (10, after adjusting for BMI), and the decrease was 20+ % (i.e., really large) for 7 of them.
  • There are obvious concerns with such a study, including the fact that they compared only the top 10th percentile to the lowest 10th percentile of leisure-time activity, which also likely includes more unaccounted-for biases (e.g., those in the highest percentile group being much more likely to have generally healthy lifestyles, which may not be fully reflected in the multivariate analysis). Also, as with any meta-analyses, there are bound to be significant differences in the methodology of each individual study, making the strict combination of them less rigorous. The measures of physical activity were self-reported, and the cutpoints of high vs low varied between the individual studies. Also, some of the measurements (e.g. BMI) were considered as dichotomous variables (either above or below 25) which could conceal their true contribution (i.e. a BMI of 25.1 may confer a very different risk from a BMI of 35.1; on the other hand a BMI of 24.9 may not be so different from a BMI of 25.1)
  • Another issue is that leisure-time activity reflects only part of the picture. Many of the old studies only looked at leisure-time activity because they could not figure out how to incorporate work-related activity into the metric. Work-related activity requires very detailed analyses of individual workplaces, given that people doing the same job in different workplaces may have amounts of physical exertion, depending on such factors as degree of automation, how large the workplace is and what the division-of-labor is, and, in general, how the specific job was structured, including the role of labor unions requiring employers to decrease the intensity or potential risks of many jobs. Also, since leisure-time activity typically reflects voluntary participation that would reinforce the above-stated potential bias that these people lead generally healthier lifestyles.
  • Another recent systematic/meta-analysis (see 174 world-wide studies, looked at the levels of total physical activity (leisure-time, occupational, domestic, transportation) and the risk of breast cancer, colon cancer, diabetes, ischemic heart disease, and ischemic strokes, finding:
    • Overall, major gains for all outcomes occurred at lower levels of physical activity (3000-4000 MET minutes/week)
    • Even 600 MET/week (the lowest level in the studies), had a 2% lower risk of diabetes (vs no reported physical activity)
    • But going from 600 to 3600 MET minutes/week reduced the risk additionally by 19%. further increases did not add much (e.g., 0.6% if increase from 9000 to 12000 MET minutes/week)
    • At higher levels of physical activity (>8000 MET minutes/week), they found:
      • 14% reduction in breast cancer
      • 21% reduction in colon cancer
      • 28% reduction in diabetes
      • 25% reduction in ischemic heart disease
      • 26% reduction in ischemic stroke
    • But, looking at the curves: for all endpoints but breast cancer, there was the most dramatic improvement going from about 1500 to 4000 MET minutes/week, with leveling off thereafter. For breast cancer, the curve showed a relatively linear decline with more activity. [Remember: this study included all physical activity: i.e. it is hard to translate the current US recommendation of 75-150 minutes/week of exercise into the above 1500-4000 MET minutes/week.]​
  • Potential mechanisms connecting exercise with decreased cancer include: decreased body fat (body fat could confer various risks, including increased estradiol levels; they did note that BMI did decrease the association with several cancers, however I would add that BMI is not the most specific measurement of body fat, and does not differentiate from the much more metabolically active and less healthy visceral fat from subcutaneous fat); also many/most hormonal systems are changed with exercise, including cortisol levels (which in themselves affect most other hormone levels), male and female sex steroids, insulin and insulin-like growth factors, and adipokines (and many of these hormone systems could be related to carcinogenesis, e.g. by altering immune function); as well as changes in inflammation, oxidative stress (which are especially related to  visceral fat), and the reduced colonic transit time which could affect colon cancer incidence.

So, a pretty quick and dirty study, but it does really reinforce the potential role of exercise in cancer prevention. This becomes even more of an issue given the predictions that the global cancer burden will increase dramatically (one model suggesting a doubling by the year 2030), especially as unhealthy lifestyles such as smoking and poor diet increase in resource-poor countries: there are increasing obesity trends and less physical activity as more people move to crowded and often quite polluted cities — these changes are associated with a pretty dramatic shift from mortality associated with infectious diseases to that associated with chronic, western-type diseases).

From blog of 1/3/17 on cardiovascular fitness as a vital sign:

  • As a quick guide to METs:
    • Light activity (<3 METs): includes walking 2.5 mph (2.9 METs)
    • Moderate activity (3-6 METS): includes walking 3.0 mph (3.3 METs), walking 3.4 mph (3.6 METs), stationary biking (light effort) 5.5 METs
    • Vigorous activity (>6 METs):  jogging (7.0 METs), calisthenics/pushups/situps (8.0 METs), rope jumping (10.0 METs)​

Primary Care Corner with Geoffrey Modest MD: understated cervical cancer mortality and hpv in men

16 Feb, 17 | by EBM

By Dr. Geoffrey Modest

2 recent articles looked at US cervical cancer mortality and hpv infections in men.

  1. The New York Times reported a huge racial gap in cervical cancer deaths in the United States (see ). They referred to an article which calculated a much higher death rate from cervical cancer overall in the US than previously found, with an increased disparity between black and white women (see DOI: 10.1002/cncr.30507).


  • The age-standardized rate for cervical cancer death reported by the National Center for Health Statistics from 2000-2012 was 3.2/100K in white women and 5.7/100K in black women
  • However, these results were not corrected for the prevalence of hysterectomies, and given that hysterectomies are significantly more common in black women, the above statistics understated the cervical cancer death rates (since these cancers are essentially eliminated in people who’ve had hysterectomies for benign reasons, especially if the cervix is removed).


  • The overall prevalence of hysterectomies was 20% for women >20 years old, higher in black women for all ages between 45-69, peaking for both white and black women at ages 65-69, but this peak hysterectomy rate was 58% of black women vs 43% of white women [remarkably high numbers overall and shockingly so for older black women!!]
  • Correcting for the prevalence of hysterectomies, the mortality rate was 10.1/100K in black woman and 4.7/100K in white women.
  • Based on this, the disparity in mortality rates was underestimated by 44% over the published NCHS numbers.
  • The highest corrected rate was in black women > 85 years, with a death rate of 37/100K vs 11/100K for white women!!!
  • Using this corrected analysis, the rate of cervical cancer deaths in white women decreased at 0.8% per year, whereas for black women the annual decrease was 3.6%.


  • Each year more than 12,000 women in the US are diagnosed with cervical cancer and more than 4000 women die from it.
  • For the women in this study, the likelihood of a supracervical hysterectomy (i.e., leaving the cervix) was <2% (data from before 2004), though now is closer to 4-7.5%. So more individual data, even if available, would not have altered the results much
  • Cervical cancer is largely preventable through screening, and screening rates may be lower in poor and minority areas, although published results on this are equivocal. The data are clearer that black women tend to present with more advanced disease and may receive different treatments than white women, e.g. less surgery and more radiation for the same stage of cancer. For example, a recent large study of more than 15,000 patients with advanced cervical cancer found that more than half did not receive treatment considered to be standard of care, mostly those who were black and poor.
  • The corrected cervical cancer mortality rates in black American women is similar to those of many resource-poor countries in Latin America, Asia (excluding Japan), the Caribbean, and Africa (including sub-Saharan Africa). For white women, their corrected cervical mortality rates are similar to those of Europe, Australia, and Japan
  • The corrected mortality is significantly higher in black vs white women in all age groups, except those aged 20-29 and 35-39 (though increases pretty dramatically in women older than this)
  • Some of the methodologic weaknesses of the study include the potential for biases related to incomplete data and the merging of 2 unrelated databases with very different methodologies. The data on age-standardized death rates came from the National Center for Health Statistics (they also looked at the SEER database, which did not include every state and notably did not include Louisiana), whereas the data on hysterectomy prevalence came from the Behavioral Risk Factor Surveillance System survey, which is based on interviews.
  • It was quite striking to me when I was working in Chicago many many years ago that a very large number of my middle-aged to older black female patients had had hysterectomies when living in the Southern US, but were unaware they even had the surgery (many reported having had some surgery, but were never told that the doctors had done a hysterectomy). We were told that this was a not uncommon method of enforced birth control for black women…. So, since some were unaware they even had the surgery (and may be part of the older women now), the racial disparity may be even greater.

So, it is quite striking that black women in the United States have such a high death rate from cervical cancer. And, perhaps a real concern is that with the repeal of the Affordable Care Act, which does cover such screenings, there may be less access for many people for appropriate screenings. In addition, I am very concerned that the upcoming, likely attacks on Planned Parenthood and other clinics providing cervical cancer screening etc., will decrease access especially for poor women and women of color.

Relevant prior blogs: which reviews the American Society of Clinical Oncology guidelines presents data from a study in the Netherlands, suggesting that negative cervical HPV screening in women over age 40 supports a strategy of screening every 10 years which was a review of urinary screening for HPV, with my concern that clinicians will be doing far fewer pelvic exams (which certainly has its pluses, since these can be invasive and uncomfortable procedures for women), but with the caveat that I have seen several younger clinicians feeling less comfortable doing pelvic exams even when clinically indicated presents a study suggesting that we should do Pap smears in HIV patients, even post-hysterectomy


  1. Another article came out looking at the prevalence of genital HPV infections as well as vaccination rates in US adult men, from the National Health and Nutrition Examination Survey (NHANES) of 2013- 2014 (see doi:10.1001/jamaoncol.2016.6192).


  • NHANES collects information of representative cross-section samples of the US population.
  • 1868 men aged 18 to 59 were examined and DNA was extracted from self-collected penile swab specimens for HPV genotype.
  • Demographic and vaccination information was gathered by self-report.


  • The overall general HPV infection prevalence in males aged 18-59 was 45.2% (i.e., 34.8 million men). bimodal pattern, with peaks age 28-32 and another 58-59
  • The infection prevalence with at least one high risk HPV subtype by DNA testing was 25.1%
  • The overall prevalence of infection for subtypes covered by the HPV-9 valent vaccine was 15.1% (the 9-valent vaccine covers 90% of subtypes responsible for cervical cancer in women)
  • The specific very high-risk subtype prevalences: 4.3% for HPV-16 (3.3 million men), 1.7% for HPV-18 (1.3 million men)
  • In vaccine-eligible men, the prevalence of infection with at least one HPV strain targeted by the HPV-4 valent vaccine was 7.1% and by the HPV 9-valent vaccine was 15.4%
  • Among vaccine-eligible men, HPV vaccination coverage was 10.7% (i.e. more than 25 million vaccine-eligible men did not receive the vaccination)


  • HPV is the most commonly known sexually transmitted infection in the US. An estimated 79 million people in the US are infected with HPV, half of new infections occurring before age 24. There was a study about 10 years ago finding that 50% of women in their first year at college acquired HPV infection. In men, an estimated 160,000 are infected annually with low-risk HPV infections
  • In men, an estimated 9000 HPV-related cancers occur annually, responsible for 63% of penile cancers, 91% of anal cancers and 72% of oropharyngeal cancers (the oral HPV infection rates are around 10% for men and 4% for women). HPV can also cause recurrent respiratory papillomatosis
  • Men seem to clear HPV infection pretty quickly, with a study of 290 men finding that the 12-month risk of acquiring a new infection was 29%, with the median time to clearance being 5.9 months (Giuliano AR. J Infect Dis 2008; 198: 827). So, it seems likely that the point prevalence in the above study significantly understates the life-time acquisition rate for HPV, which is similar to that of women.
  • BUT, the major public health issue for men is that they can transmit this infection to women, potentially leading to cervical cancer, with a significant morbidity and mortality (as in first article above)
  • The CDC therefore published their recommendations for HPV vaccination: females aged 11 to 26; males aged 11 to 21, but from 21-26 being “recommended for persons with a risk factor (medical, occupational, lifestyle, or other indication”). Probably makes sense to support male vaccination till age 26, similar to the female recommendations

So, bottom line: these studies are very concerning, since on the one hand HPV infections are wide-spread and the number of unvaccinated men who are vaccine-eligible is staggering; on the other hand, cervical cancer death rates are quite high in the US and with a pretty dramatic black-white differential.

Primary Care Corner with Geoffrey Modest MD: Is Mammography Useful?

14 Feb, 17 | by EBM

By Dr. Geoffrey Modest

This blog will bring up 2 recent studies suggesting the lack of efficacy of mammography screening coupled with significant overdiagnosis.

  1. An article a couple of years ago looked at screening mammography in the US, with 10 year follow-up of breast cancer incidence and mortality (see Harding C. JAMA Intern Med 2015; 175: 1483).


  • This was an ecological study of 16,120,349 women 40 years of older who resided in 547 counties reporting in the Surveillance, Epidemiology, and End Results (SEER) cancer registries during the year 2000.
  • 53,207 had a diagnosis of breast cancer and were followed for 10 years.
  • The researchers looked at the extent of the screening in each county, and the results of both breast cancer incidence and mortality (the latter being defined as women diagnosed with breast cancer in the year 2000 who had died from the disease during the 10 year follow-up period). Overall, in the 547 counties, the overall 10-year incidence based mortality was 47.2 per 100,000 cases diagnosed in 2000.


  • There was a strong positive correlation between the extent of mammography screening and the breast cancer incidence (P<0.001)
  • But, there was no relationship between screening and breast cancer mortality.
  • Each increase of 10 percentage points in the extent of screening was accompanied by:
    • A 16% increase in breast cancer diagnoses, RR 1.16 (1.13- 1.19)
    • Not even a trend to a change in breast cancer deaths, RR 1.01 (0.96-1.06)
  • Analyzing by tumor size, screening led to a higher incidence of small breast cancers (<= 2 cm), but not with a decreased incidence of larger breast cancers (>2 cm )
  • Each increase of 10 percentage points in screening is associated with:
    • A 25% increase in the incidence of small breast cancers, RR 1.25 (1.18- 1.32)
    • A 7% increase in the incidence of larger breast cancers, RR 1.07 (1.02- 1.12)
  • The following figure shows that as the proportion of women had a mammogram in the past two years, the incidence of breast cancer diagnoses increased significantly yet the 10-year mortality did not budge


  • So, pretty powerful large-scale epidemiologic study, finding that mammography led to a large increase in the diagnosis of small cancers, but there was no decline in the detection of larger cancers. This may be the reason why there was no significant difference in the overall death rate from breast cancer by doing mammography screening.
  • What does this mean? It may mean that there are a subset of very aggressive small cancers which spread and cause clinical disease and mortality, and that screening is didn’t help for these. And that a very large number of small cancers that are picked up by mammography are in fact “overdiagnosed” (defined as: tumors that would not have become clinically evident in the remaining lifetime without screening).
  • One would have expected that if screening did pick up small tumors earlier, that over time the diagnosis of larger and less treatable cancers should decrease. It is quite concerning that the number of larger breast cancers in fact continued to increase over the study. And, of course, the goal of screening is to reduce mortality, which was not found in the study. One additional finding was that increased screening would lead to more breast conserving surgical procedures; however they found no evidence of a decrease in extensive mastectomies.
  • Without getting into a lot of detail, the authors present reasonable arguments that this is not just lead-time bias, or ecological bias (this latter happens when looking at group data and assuming that it applies to the individual who may or may not have had a mammogram). Also, there was no association between mortality rates even comparing those counties with much higher breast cancer incidence, reducing the potential bias of comparing counties with very different incidences of breast cancer. But, they also did not have data on women who had therapy or what the risk factors were for the women who developed breast cancer. Also, this was just a 10-year follow-up, and patients may well live more than 10 years with newer therapies, but I would have expected some evident benefit of screening by 10 years (and at least a trend to benefit…)
  • There have been several important changes in technology over the past several decades, some of which may make older studies less applicable now (these older studies are the ones on which current mammogram recommendations are based). On the one hand, the sensitivity of our screening methods is greater and we are picking up much smaller tumors; and, perhaps these smaller tumors are more likely to regress than the larger ones picked up previous, leading to increased overdiagnosis. On the other hand, treatments have improved a lot, and the risk/benefit equation may have changed some. Given the potential harms of overdiagnosis (including surgery, radiotherapy, and chemotherapy), we should be looking at the new balance. In addition, there are interesting advances in genomic profiling, which are helpful in determining how aggressive a tumor is likely to be as well as how intensive therapy should be

So, a large study like this offers interesting insights, especially when looking at likely overdiagnosis (which one cannot determine in an individual patient). As with all screening tests (e.g. PSA), it would be really useful to figure out how to risk stratify patients, with more aggressive screening in those at higher risk. That is much more likely to show benefit for screening then with screening the general population.


  1. A more recent article look specifically at breast cancer overdiagnosis by mammography screening in Denmark (see doi:10.7326/M16-0270)). The study looked at women aged 35 to 84, from 1980 to 2010.


  • Denmark had a perhaps unique opportunity to look at the results of mammography screening both because it has rigorous databases (the Danish Breast Cancer Group, DBCG, and the Danish Cancer Registry, DCR) as well as a 17-year screening program which involved 20% of the population aged 50 to 69. This differential access to mammography screening allowed for real-world comparisons to a large, essentially randomized non-screening populations. Clinical breast exams were not included.
  • The DBCG database included 90,665 women aged 35 to 94 who were diagnosed with invasive breast cancer, and 4267 diagnosed with DCIS
  • For the mammography group in DBCG, they divided tumors into two groups: large (>20 mm) and small (<20 mm), considering the large tumors as “advanced” because they are equivalent to T2 or greater in the TNM classification system
  • The screening routine, somewhat different from what we do in the US, was biennial screening with a 2-view mammography on the first round, with 1-view mammography at subsequent screens except for women with dense breasts who always received a 2-view mammogram.
  • The DCR provided individual data on tumor size in women with invasive breast cancer.


  • For women aged 35 to 69: in non-screening areas the incidence of advanced cancer increased throughout the observation period.
  • For women 70 to 84: in the non-screening areas the incidence of advanced cancer also increased throughout the observation period, and was most pronounced in the later years.
  • The incidence of non-advanced tumors increased in the screening versus prescreening periods, incidence ratio 1.49 (1.43- 1.54), i.e. a 49% increase
  • Looking just at nonadvanced tumors, there were 711 invasive tumors and 180 cases of DCIS that were overdiagnosed in 2010 (overdiagnosis rate of 48.3% including DCIS and 38.6% excluding DCIS
  • There was no reduction in the incidence of advanced cancers through mammography screening.
  • Their conclusion: “it is likely that one in every three invasive tumors in cases of DCIS diagnosed and women offered screening represents overdiagnosis (incidence increase of 48.3%)”


  • This study is quite remarkable since it is reasonably close to a really large-scale randomized controlled trial, in which for 17 years 20% of women got mammograms and the rest didn’t. And there was no difference in advanced breast cancers through consistent mammography screening
  • See below for other blogs on the poor utility of mammography screening, also showing almost no decrease in breast cancer mortality but large numbers of overdiagnosed mammogram-detected cancer.
  • A lot of the “overdiagnosis” is from DCIS (about 25% of all new breast cancer diagnoses), which the National Cancer Institute now classifies as a “noninvasive condition” (an observational study of 108,196 women with DCIS in the SEER registries found an overall breast cancer death rate of 3.3% over 20 years, similar to the general population: see Narod SA. JAMA Oncol 2015; 1(7):888
  • All of this reinforces the fact that early detection of breast cancer is fraught. For breast cancer, there are 230,815 diagnoses/year in women, 2109 in men; and 40,860 breast cancers deaths/year in women and 464 in men, and affects 1 in 8 women!!!; yet mammography screening has perhaps minimal benefit. Which really brings up the issue of prevention (which, it turns out, does not get much funding). As noted in prior blogs, one big unknown is the prevalence of industrial toxins (many of which are estrogenic, including pesticides, BPA, others used in plastics, etc etc) which are in our environment and may well be carcinogenic. Large numbers of new chemicals are being used and thousands of new ones are introduced each year with minimal attempts to look at potential toxicity. In addition, it is reasonably clear from the studies that healthy diet, weight control, and exercise are helpful. It seems to me that it would likely be much more useful to devote our national resources into preventing breast cancer by regulating environmental toxins and promoting healthy lifestyles than attempting early detection.

See which documents the quite remarkable discordance in radiologists’ reading of breast densities

See​ for the 25-year results from the Canadian National Breast Screening Study finding NO benefit from mammography screening but that 22% of mammography-detected breast cancers were overdiagnosed.

See for a 2014 meta-analysis, finding that mammography yielded very small changes in breast cancer mortality (e.g. screening women in their 50s would lead to 3-32/10,000 decrease in breast cancer mortality, but have 6130 false positive and 30-137 overdiagnoses)​. As mentioned above, these studies were older ones.

Primary Care Corner with Geoffrey Modest MD: Cardiovascular Fitness — a new vital sign?

19 Jan, 17 | by EBM

By Dr. Geoffrey Modest

A recent scientific statement from the American Heart Association stresses the importance of assessing cardiorespiratory fitness (CRF) as part of the risk assessment for cardiovascular disease (see DOI: 10.1161/CIR.0000000000000461)​.


  • Studies since the 1950s have consistently found that CRF is a strong and independent marker of cardiovascular risk as well as all-cause mortality, adjusting for age and the other standard risk factors. This is been found in healthy men and women, those with known or suspected cardiovascular disease, and those with the co-morbidities of obesity, type 2 diabetes, hypertension, and hyperlipidemia. In many studies CRF is a more powerful predictor of mortality risk than traditional cardiovascular risk factors. It has even been shown to be a more powerful risk predictor than ST-segment depression, cardiovascular symptoms, or hemodynamic responses.
  • The survival benefit in 13 studies showed that each 1-MET (metabolic equivalent) higher CRF, a small increment, was associated with a marked 10-25% improvement in survival. And, one study found that men who improved from unfit to fit between two successive examinations had a reduction in mortality risk of 44% relative to those who remained unfit in both exams (i.e., those with higher CRF have dramatic clinical benefit)
  • As a quick guide to METs:
    • Light activity (<3 METs): includes walking 2.5 mph (2.9 METs)
    • Moderate activity (3-6 METS): includes walking 3.0 mph (3.3 METs), walking 3.4 mph (3.6 METs), stationary biking (light effort) 5.5 METs
    • Vigorous activity (>6 METs):  jogging (7.0 METs), calisthenics/pushups/situps (8.0 METs), rope jumping (10.0 METs)
  • Of note, even though the most dramatic differences in all-cause and cardiovascular mortality were found comparing the most fit to the least fit subjects (70% and 56% respectively), the greatest increase in mortality benefit was in comparing the least fit group to the next least fit category
  • A recommendation in the paper is that CRF should become an accepted “vital sign”, and should be part of the standard clinical encounter
  • CRF also is associated with heart failure exacerbations and mortality, with one study finding that for every 6% increase in CRF over three months there was a 4% lower risk of cardiovascular mortality or hospitalization, and an 8% decrease risk of cardiovascular mortality or heart failure hospitalization (for example, see which shows the benefit of vigorous exercise in patients with heart failure and reduced ejection fraction), timing of cardiac transplantation, preoperative surgical risk prediction (including studies of abdominal aortic aneurysm repair, liver transplant, lung cancer resection, upper GI surgery, intra-abdominal surgery, bariatric surgery, coronary artery bypass grafting). And interventions seem to help: in patients waiting for CABG surgery, those randomized into an exercise training group had superior outcomes to the control group, with a reduced rate of perioperative complications and shorter hospital stays. And observational studies have also shown that men with higher CRF had 68% lower stroke mortality, controlling for standard risk factors.
  • There were a few studies showing that those with a higher level of CRF had a reduced risk of developing dementia or Alzheimer’s, one study showing a 36% lower risk of developing dementia in those with the highest quartile of CRF. Higher levels of CRF are also associated with lower measures of anxiety or depression symptoms
  • Many studies have shown decreased risk of development of prediabetes, metabolic syndrome, and type 2 diabetes in those with higher CRF, again with the biggest difference in those going from lower CRF to the moderate range.
  • Lower levels of CRF at a younger age are also associated with a higher risk of disability at an older age. For example one study of obese adults with type 2 diabetes found that after four years, improvement of CRF decrease the likelihood of developing disability
  • Added value of CRF to the traditional risk calculators:
    • Several analyses have looked at various ways of incorporating the additional value of CRF. In one 30-year study of patients with stage II hypertension, the 30 year risk of cardiovascular mortality was 18.4% in those with low CRF versus 10.1 present in those with high CRF (i.e., a huge difference)
    • Overall, adding CRF to the traditional risk stratification led to actual CVD and all-cause mortality outcomes being correctly reclassified through the risk predictor as being decreased 23.3% and 20.6% respectively through correctly reclassifying patients as higher risk, and 55.8% and 46.0% respectively for correctly reclassifying patients as lower risk. The overall changes reflected a 30.5% and 24.5% correct reclassification for all-cause mortality, with larger changes in correctly reclassifying patients as lower risk because of CRF. [e., those at apparently high risk by a traditional risk calculator, in reality have significantly lower risk if they are more fit; there are changes apparent in the other direction as well, but less emphatically so]. Also as a point of comparison, when looking at the nontraditional risk factors, such as coronary artery calcium scores  (which seems to be the best of the lot), the level of correct reclassification from the traditional risk calculators is much lower
  • So, how does one measure CRF?
    • The most accurate and standardized quantification of CRF is through CPX (cardiopulmonary exercise testing), a combination of conventional exercise testing with ventilatory expired gas analysis
    • A step below that is to look at achieved treadmill speed/grade and duration, making sure the patient does not hold the hand rails
    • Another approach is to look at submaximal exercise testing or the 6-minute walk test to assess distance walked (walking <350 meters is associated with high risk).
    • And the easiest overall/least time-consuming/cheapest/easiest to implement is to do nonexercise prediction calculations. These are not standardized at this point, and each study seems to have somewhat different calculators. Perhaps the best is to use the one by Nes BM. Med Sci Sports Exerc 2011; 43: 2024, which incorporated an assessment of patient reported physical activity, age, waist circumference, and resting heart rate, and this is one of the studies which included a lot of people (n= 2067 men and 2193 women) and looked at actual clinical outcomes, finding that 90.2% of women and 92.5% of men in the lowest two quartiles of fitness were correctly classified. Their questions for physical activity included: frequency of exercise (never, <1x/wk, 1x/wk, 2-3x/wk, >3x/wk), intensity (“no sweat/heavy breathing, “heavy breath and sweat”, “push myself to exhaustion”), and duration (<15 in, 15-30 min, 30-60 min, >60 min).
    • Overall exercise recommendations:
      • Type: exercise should involve major muscle groups (legs, arms, trunk) that is continuous and rhythmic (e.g. brisk walking, jogging, cycling, swimming, rowing)
      • Intensity: moderate and/or vigorous intensity relative to the persons capacity
      • Frequency: at least five days per week of moderate or three days per week of vigorous intensity exercise
      • Time: 30 to 60 minutes per day (150 minutes per week) of moderate and 20 to 60 minutes per day (75 minutes per week) of vigorous exercise. Of note between 10 and 20 minutes can be beneficial in previously inactive people
      • Amount: a target of 500 to 1000 MET-min/wk
      • Pattern: one continuous session per day or multiple sessions per day of greater than 10 minutes each. Less than 10 minutes may work in deconditioned individuals.


  • Incorporating CRF reflects a more individualized physiologic approach (assessing the constellation of how well the heart, lung, circulation, and oxygen extraction by muscles works). It is clear from epidemiologic data that on a community basis, as well as individual basis, the traditional risk factors of smoking, hypertension, hyperlipidemia, and diabetes confer an increased risk of cardiovascular disease. However, CRF is a truly specific individual physiologic risk factor, reflecting how these risk factors and more play out in the individual’s body. For example, hypertension itself confers different levels of individual risk dependent on CRF.
  • One note of caution: there is no uniformity in clinical practice as to which of the traditional risk calculators is the best: the Am Heart Association/Am College of Cardiology just published an updated tool, including a spreadsheet calculator (see org/10.1161/CIR.0000000000000467 for the article, and the spreadsheet to calculate risk. BUT, this tool also needs to be validated in different populations prior to being accepted (also, see for a critique of the 2013 ACC/AHA lipid guidelines.)
  • Interestingly, several studies suggest that CRF is a more potent predictor of cardiovascular disease than any of the individual risk factors we have incorporated into our predictive models
  • Why is CRF so important? There are several explanations: improved traditional cardiovascular risk profiles (though most of the studies did control for the major ones we know), changes in autonomic tone that may reduce arrhythmogenic risk, fewer thrombotic events (exercise decreases fibrinogen levels, for example), improved endothelial function, lower levels of visceral adiposity/improved insulin sensitivity, lower levels of inflammation, as well as perhaps improved mental health and sense of well-being. And, there might be important positive changes in the gut microbiome with exercise, which is clear in animal models, less clear in humans where those who exercise tend to eat differently from those who do not, so hard to control well).
  • I should add a couple of caveats here: it is important not to confound fitness with doing lots of exercise; a significant component of fitness (on the order of 30+%) is genetic and not related to regular exercise. And most of the studies above are observational, not intervention studies (i.e., only a few actually randomized patients to exercise programs vs none and looked at long-term outcomes. Though the one on pre-surgery exercise programs was pretty impressive. And, the overall data on the benefits of exercise overall are quite robust)
  • For ballpark figures, those with a CRF level less than 5 METs have a particularly high risk of mortality, whereas those with CRF levels of greater than 8 to 10 METS seem to have much more protection. And, more than half the reduction in all-cause mortality occurs between those who are least fit (e.g. CRF less than 5 METs) and those in the next least fit group (e.g. CRF 5-7METS); i.e., benefits for cardiorespiratory fitness are particularly strong in those people in the least fit as compared to the next higher category (i.e., one does not need to be an Olympic athlete to achieve the benefits)

So, the key points here are:

  • Cardiorespiratory fitness is an independent in additive risk assessor for total and cardiovascular mortality
  • Improving CRF dramatically decreases cardiovascular and all-cause mortality
  • This clinical improvement is especially profound in those who are the least fit, finding a greater than 50% risk reduction by moving one step up to the next least fit group. An increase in CRF of only one MET is associated with the 10 to 20% decrease in mortality rate
  • There is a reasonable argument based on studies that have been done to propose that a simple, non-exercise based calculator should be added as a vital sign. This could easily be measured by nonclinical staff and would provide clinicians important information to help encourage patient-specific exercise programs. This should to be evaluated more completely in different populations to assess its generalizability. However, even without those studies, given the documented benefits of exercise and the dramatic relationship in the above studies of CRF as a risk predictor, I personally will ask patients about CRF more and further reinforce the importance of exercise as part of a healthy lifestyle.

For other blogs on exercise, see

Primary Care Corner with Geoffrey Modest MD: calcium intake does not increase cardiovascular risk

13 Dec, 16 | by EBM

By Dr. Geoffrey Modest

A recent guideline from the National Osteoporosis Foundation and the American Society for Preventive Cardiology, with support from an independent evidence review team from Tufts University, determined that calcium supplementation, with or without vitamin D, had no relationship to cardiac health (for the recommendations see doi:10.7326/M16-1743; for the full document see doi:10.7326/M16-116).


  • calcium with or without vitamin D intake from food or supplements has no relationship (beneficial or harmful) with the risk for cardiovascular and cerebrovascular disease, mortality, or all-cause mortality in generally healthy adults at this time
  • Calcium intake should not exceed the National Academy of Medicine recommendations of 2000-2500 mg/d
  • Obtaining calcium from food is preferred to taking supplements
  • This recommendation is supported by a review of the human studies and is supported mechanistically and pathologically in animal studies on high-calcium diets (no biological mechanism supports the association between calcium intake and cardiovascular disease).


  • It is clear that calcium and vitamin D are necessary for adequate bone health. However several recent studies have questioned whether fractures were reduced by supplementation in older adults. There even have been reports that cardiovascular disease, including MIs and strokes, may be worse by supplementation (more below).
  • This review included 4 randomized controlled trials, one nested case-control study and 26 cohort studies.
  • Of note, very few studies looked at calcium intakes of greater than 1600 mg per day. One study that did do so, found that there was no increased cardiovascular disease (CVD) or mortality in those at the highest level of calcium by the combination of foods and supplements, but a somewhat increased risk in those on supplements only. However, for strokes there was a lower risk for all types of consumption.
  • There are several general concerns raised by all of these dietary studies:
    • They are usually dependent on dietary recall/food frequency questionnaires, often at only a few points in time, and dietary recall itself is not necessarily so accurate
    • It is really impossible in observational studies to isolate specific dietary ingredients or vitamins. Although analyses try to look at likely confounders, there are undoubtedly unanticipated ones (are those who have more calcium and vitamin D in their diet more likely to be health-conscious and also have a lower morbidity/mortality related to that? Or, contrarily, do those who are the least health-conscious take supplements to boost their calcium and vitamin D because they just heard on the news that this was important and might counteract their less healthy lifestyle?). It is interesting that in the one study with the highest levels of calcium intake, there was divergence between those who had calcium by foods versus supplements in terms of CVD and mortality. Perhaps those on supplements had generally less healthy diets? Or is there a fundamental physiologic difference between getting calcium from food versus pill (which appears to be different for CVD and stroke outcomes)??
    • The dietary studies themselves are often given equal weight, when some are better studies in others. For example, it is notable in the above that even the inconsistent association between calcium and/or vitamin D and CVD outcomes is more apparent in subgroup analyses than in the overall trials. And some showing lack of benefit for bone studied people with already adequate 25(OH)D levels to begin with (i.e. supplements might not do much more).
    • One cited concern is that increased calcium might lead to more vascular calcification. But this was derived from studies of persons with pretty severely impaired renal function on several meds, and not the general population.
    • As noted in prior blog (see ), there are real concerns about the value of meta-analyses/systematic reviews. Of course, there also limitations of single trials, or the latest trial that makes it into the journals and popular press. This current study was a truly independent meta-analysis, conducted by a well-respected group, and the evaluation of the individual studies they included pretty impressively confirmed that calcium intake is safe, even up to the 2000 to 2500 mg per day range (but the studies are pretty limited on this, as noted above).
    • The current meta-analysis did raise pretty serious methodologic concerns about 2 recently published reports finding adverse cardiovascular outcomes with calcium supplementation with or without vitamin D
  • There is also some confusion in the medical literature about the benefits of vitamin D in terms of fall prevention (see which critiques a recent study). The USPSTF most recent guidelines (prior to this study) still noted “that vitamin D supplementation is effective in preventing falls in community-dwelling adults aged 65 years or older who are at increased risk for falls”.

So, putting this all in perspective, I think that it is clear that bone health requires adequate vitamin d and calcium levels. Guidelines differ in their specific recommendations:

  • Some suggest achieving a 25(OH) vitamin d level of 20 ng/ml and some suggest 30 ng/ml.
    • The USPSTF in 2013 found insufficient evidence to recommend >400 IU vitamin D or >1000 mg of calcium (though it warns against supplementation with <= 300 IU vitamin D or <= 1000 mg calcium)
    • The Endocrine Society (see doi: 10.1210/jc.2011-0385) suggested checking 25(OH) vitamin d levels in people at high risk for deficiency, with deficiency defined as <20ng/ml (50nmol/L), and in general recommends:
      • For children <1yo, at least 400 IU/d; for 1-18 yo, at least 600 IU/d. but not enough reliable data to raise the 25(OH)D level to 30 ng/ml
      • For those 19-50yo, at least 600 IU/d, but might need 1500-2000 IU/d to achieve consistent levels >30 ng/ml
      • For those 50-70yo, at least 600 IU/d,but might need 1500-2000 IU/d to achieve consistent levels >30 ng/ml
      • For those >70yo: at least 800 IU/d. but might need 1500-2000 IU/d to achieve consistent level
      • For pregnant/lactating women, at least 600 IU/dbut might need 1500-2000 IU/d to achieve consistent levels >30 ng/ml
      • And more aggressive therapy (e.g. 2000IU/d) for those who are vitamin D deficient
  • For calcium, the NIH recommends (which is pretty similar to the Institute of Medicine):
    • Age 1-3: 700mg/d
    • 4-8 yo: 1000 mg/d
    • 9-19 yo 1300 mg/d
    • 31-70yo 1000 mg/d
    • But 51-70yo women and everyone >70yo: 1000 mg/d

I personally do suggest to patients that they consume a high calcium diet, but this is often limited by cultural or other circumstances (e.g., lactose intolerance). And, it is hard for those living in the Northeast to get adequate sunlight for adequate vitamin D levels (and I still shoot for 30 ng/mL as a target). So, though I would prefer all calcium and vitamin D coming from natural sources (diet, sunlight), most of my patients are on supplements. And usually taking 1 tablet of calcium 600mg combined with vitamin D 400IU twice a day is adequate (though I do have some high risk patients, including those with low Bone Mineral Density, who need 2000 IU of vitamin D/day). And I do check 25 (OH) vitamin D levels in those I think are at high risk (BMD, history of fragility fracture, medications, very limited outside sun exposure, etc.).

Primary Care Corner with Geoffrey Modest MD: Colonoscopy Screening in the Elderly?

10 Nov, 16 | by EBM

By Dr. Geoffrey Modest

A recent observational study of Medicare recipients found that those 70-79 years old seemed to benefit from colorectal carcinoma (CRC) screening (see doi:10.7326/M16-0758). Study sponsored by the NIH.


  • 1,355,692 Medicare beneficiaries (from 2004-2012) aged 70-79, who were of average CRC risk, assessing 8-year risk for CRC and 30-day risk for adverse events.
  • Average risk was defined as: no history of adenoma, IBD, colectomy, and no colonoscopy/sigmoidoscopy/fecal occult blood in the past 5 years; and no prior abdominal CT, diagnosis of anemia, GI bleed, other GI symptoms, weight loss within the past 6 months
  • Included were those who were “health-conscious”, defined as having received at least 2 of the 3 preventive annual Medicare serviced of annual wellness visit, influenza vaccine, and breast or prostate cancer screening


  • 70-74yo, 8-yr risk of CRC was 2.19% (2.00 to 2.37%) in the screening group vs 2.62% (2.56 to 2.67%), so absolute difference of -0.42% (-0.24% to -0.63%)
  • 75-79yo, 8-yr risk of CRC was 2.84% (2.54 to 3.13%) in the screening group vs 2.97% (2.92 to 3.03%), so absolute difference of -0.14% (-0.41% to +0.16%) – i.e. nonsignificant
  • 70-74yo, excess 30-d risk of adverse events with colonoscopy was 5.6 events per 1000 people (4.4 to 6.8)
  • 75-79yo, excess 30-d risk of adverse events with colonoscopy was 10.3 events per 1000 people (8.6 to 11.1)


  • The current guidelines, as in many guidelines, varies by who is writing them. The USPSTF currently recommends screening by any of several methods, from 50-75 yo in those at average risk (evidence grade “A”, with individualized decisions in those 76-84, though the evidence grade here was “C”, meaning that they recommend”offering or providing this service to individual patients based on professional judgment and patient preferences. There is at least moderate certainty that the net benefit is small”
  • There are several concerns about drawing major conclusions from this new NIH-sponsored study:
    • Although there are 132,000 new cases of CRC in the US per year and 50,000 CRC-related deaths, it is not clear to me that this proportion applies in the more elderly population. As noted in this study of “health conscious” elderly, there was much more morbidity found in the older 75-79 yo cohort (e.g. hypertension in 80.5% vs 74.9% in the 70-74 yo, ischemic heart disease in 45.3% vs 36.6%). This increased morbidity is likely to translate to more people “dying with the cancer than dying from the cancer”.
    • All of this data is from the Medicare database, which, my guess, does not have the most accurate detailed information, and does not even have the CRC-specific mortality, a pretty useful endpoint for this study…
    • I am not so sure of the assumption that people who are more “health conscious”, as they define it, are in fact healthier/qualify as “average risk”. My guess is that the threshold for colonoscopy screening in the elderly varies lots by who the provider is (some may well push continued screening either in the undocumented belief they are helping the patient, they are uncomfortable effectively saying “you are too old to continue screening”, etc.), and some patients I see request different screens even with considerable morbidity (either they do not want to deal realistically with death/their prognosis, they are pretty somatic and want to  search for problems, etc). And, I would not be surprised if a higher percentage of less healthy patients get flu shots more aggressively (one of their “health conscious” criteria), either because of provider or patient preferences (and the fact that they come in for health care more often, with more opportunities for vaccines). Only a well-designed prospective trial would work to sort this out.
    • This study was limited to colonoscopy screening, which has been documented in the past to work much less well in the elderly, with higher numbers of inadequate preps (leading to more colonoscopies with more intensive preps), and (also perhaps related) higher perforation rates, which can lead to major abdominal surgery in an older and higher risk population. So, perhaps not the screening method of choice…
    • The stage-shift found in screening (i.e., fewer cases of more advanced CRC lesions in the screened group) certainly is supportive of screening, but again, colonoscopy is not only very expensive but quite invasive, so it really is important to look at real clinical outcomes before making a screening decision (i.e., does this stage-shift to higher stage lesions really translate to more morbidity/mortality?)
  • It seems to me to be a tad disingenuous to conclude in the abstract that “screening colonoscopy may have had a modest benefit in preventing CRC in beneficiaries aged 70 to 74 years and a smaller benefit in older beneficiaries”, but then in the last paragraph, having basically the same sentence, but with the qualification “and a smaller (if any) benefit in those who are older” (my emphasis). The reality is that many busy clinicians rely on the accuracy of the abstract and may not read the whole article, especially in primary care practice which is not only really busy, but requires clinicians to read and assimilate literature from all of the specialties. The above article also tends to minimize the adverse effects, stating they were “low but greater among older persons”. But, the rate was twice as high, and I would not be surprised if the actual effect of these adverse outcomes, in terms of resulting functional impairments, increases in an older population (they just don’t bounce back as well even from less-than-severe adverse effects).
  • And, this is really my main criticism of the take-home message of this study: I would phrase the conclusion more like “there is no clear evidence that screening colonoscopy offers any significant benefit in those 75-79 years old, that the possible benefit in terms of decreasing CRC diagnosis may translate even less into real morbidity and mortality benefit in this age group, and that there was almost a doubling of adverse events in this pretty susceptible population.” I personally do think that a healthy 79 yo, who really does have a realistic life expectancy (e.g., the healthiest 25% of women aged 80 has a 17 year life expectancy, and men 13 years), might realize actual clinical benefit by diagnosing and treating CRC early, especially since treatment for early lesions is pretty benign, but I have adopted FIT testing as my preferred non-invasive CRC testing, which should help winnow the colonoscopies and their adverse effects to a much smaller exposed group, and one with a higher yield for benefit over risks.

Primary Care Corner with Geoffrey Modest MD: Cervical Screening Guidelines From ASCO

17 Oct, 16 | by EBM

By Dr. Geoffrey Modest

The American Society of Clinical Oncology just published guidelines for the secondary prevention of cervical cancer (see doi: 10.1200/JGO.2016.006577, or go to ). These guidelines were unusual in that they stratified the screening approach based on the country’s resources, reflecting a global initiative, and also had several differences from the current US guidelines.


  • HPV testing is recommended in all resource settings, though visual inspection with acetic acid may be used in countries with basic resources.
  • Frequency of testing:
    • For countries with maximal resources: should be from age 25 to 65, every five years if negative.
    • For countries with enhanced resources: age 30 to 65. If two consecutive negative tests at five-year intervals, then every 10 years. Stop at age 65 if consistently negative results for the past 15 years
    • For countries with limited resources: age 30 to 49 every 10 years
    • For countries with basic resources: age 30 to 49, 1 to 3 times per lifetime
  • Treatment options for patients with a positive screen:
    • In countries with more than basic resources: colposcopy, then loop electrosurgical excision (LEEP) if positive
    • For countries with basic resources: treat with cryotherapy or loop electrosurgical excision
  • Follow-up post-treatment:
    • 12 month follow-up is recommended in all settings
  • For HIV-positive women (also applies to women who are immunosuppressed for any reason):
    • Overall, screen with HPV testing twice as many times per lifetime as in the general population (as above). Screening should begin as soon as they get the HIV diagnosis [? when to start if they are born with the infection/or get it from a transfusion at age 8???].
      • In countries with maximal  resources: screen with HPV every 2-3 years
      • In countries with enhanced resources: screen with HPV at 2-3 year intervals; but if negative, every 5 years (approx 8 screenings in lifetime)
      • In countries with limited resources: twice as often as in general population (4-6 screenings per lifetime)
      • In countries with basic resources: begin screening with HPV if available, or with visual inspection with acetic acid, at age 25, then every 3 years if negative initially. [A bit unclear, since they then suggest it will be approximately twice per lifetime]. These recommendations are based on murky data…
    • Postpartum screening: overall no screening recommended during the pregnancy, partly because the normal immune changes in pregnancy can have increased HPV changes which subside after pregnancy.
      • Screen at six months in all countries other than those with only basic resources, where screen at 6 weeks since longer interval could lead to loss of follow-up [though this might apply to other countries, or areas in other countries as well…..]
    • No screening should be done in people who had a total hysterectomy for benign causes [though see blog, which would support general screenings in HIV-positive women who had hysterectomy]
    • And, in countries with basic resources without mass screening — infrastructure for HPV testing, diagnosis and treatment should be developed
    • Self-screening: there is evidence that women doing their own HPV sampling may improve screening coverage, though the pooled sensitivity and specificity are lower, especially for CIN2+. So, overall not suggested except in women who might otherwise not get tested at all [and the sensitivity and specificity are actually only a little lower].
    • Postulated effect of HPV vaccine: likely to decrease the incidence of HPV 16/18 cancers, and with approx 5 year later onset of disease as a result of decreasing these most-carcinogenic genotypes, so potentially can start screening later in life, and decrease screening to ages 30, 45, 60. Maybe no need to screen at all??? Or only once??  But all recommendations are pending actual data….


  • High-quality screening programs can lower the incidence of cervical cancer by up to 80%
  • HPV is the most frequent sexually-transmitted infection, with one study finding 43% of college women getting infected over 36 months (see Ho GYF. New Engl J Med 1998; 338:423)
  • As a point of reference, the US screening guidelines at this point are quite different from the above ASCO ones for countries with maximal resources (e.g. the USPSTF recommendations):
    • Begin at age 21, do cytology screening only until age 30, and then every 3 years if normal. HPV testing not recommended because of higher likelihood of unnecessary follow-up and procedures (HPV infection tends to be transient)
    • After age 30, either continue cytology only every 3 years, or do cytology/HPV co-testing every 5 years, if normal results
    • Stop at age 65 unless there is increased risk (history of abnormal screens, prior HPV-related disease, immunocompromise, DES exposure); and if there are 2 negative consecutive co-tests or 3 negative cytologies within prior 10 years; and no history of high-grade dysplasia or worse
  • Although ASCO cites the importance of HPV testing, they do not make formal recommendations about primary HPV testing vs co-testing, noting just that some countries and regions have moved towards adopting primary HPV testing (see )
  • The American College of Obstetricians and Gynecologists also just came out with their recommendations in 2016 (though, not sure what to make of this: but these guidelines were retracted from the January 2016 issue of their publication Obstetrics and Gynecology, and I could find only recommendations for HIV-positive women, though these were also retracted), with a few differences from ASCO. for HIV infected women:
    • Start screening within one year of onset of sexual activity, but no later than age 21
    • Screening should be continued throughout a woman’s lifetime and not stop at age 65
    • For women less than 30 years old:
      • Cytology screening (without HPV testing) should be repeated in 12 months (though some people feel it should be followed in six months)
      • If three consecutive cervical cytology tests and normal, follow-up cervical cytology should be done every three years
      • If ASCUS on cytology, and reflex HPV testing is positive, then colposcopy. If HPV testing results are not available, repeat cytology in 6 to 12 months if more advanced dysplasia is found, refer for colposcopy
    • For women older than 30 years old, do cervical cytology or co-testing:
      • If only cytology is done, follow-up is as for women less than 30 years old
      • If co-testing is done and negative, repeat at three years; if cytology is negative and HPV positive, repeat in one year (though if HPV 16/18 is present go directly to colposcopy). if either of the co-tests at one year is abnormal, colposcopy
    • The hope is that as HPV vaccination becomes more widespread, the incidence of cervical cancer will decrease significantly as well as the need to screen for it; though this is in the relatively distant future, given the high prevalence of HPV infections currently, and the vaccine does not help those currently infected or with abnormal cytology from infection
    • They do recommend starting screening at age 25, as is done in several countries in Europe for example, noting that there is lack of evidence of the benefit of decreased cancer risk in those under 25 (very uncommon), and potential harm or screening and overtreatment. The United States still recommends initiation of screening at age 21. And though HPV infections are remarkably common in women under 25 (as noted in study above), HPV infections clear spontaneously, and 90 to 95% of those with even LGSIL as well as many with high-grade lesions regress spontaneously
    • And they recommend HPV screening at age 25 in countries with maximal resources, different from the general recommendations in the US to start HPV screening at age 30
    • So, my guess is that the formal US recommendations will change significantly in their next iteration (the USPSTF recommendations date from 2012, with an anticipated update 2018). Perhaps internal controversy led to ACOG retracting their guidelines??  But it is pretty clear that recently the approach to cervical cancer screening has changed significantly in other countries.

Primary Care Corner with Geoffrey Modest MD: Radiologist Variability in Mammography Readings

13 Oct, 16 | by EBM

By Dr. Geoffrey Modest

A recent article revealed the dramatic variability in radiologists’ interpretations of mammographic breast density (see Sprague BL. Ann Intern Med 2016; 165: 457). Determining breast density accurately is certainly important because increased breast density leads to difficulty in reading mammograms and is an independent risk factor for breast cancer. In this light, one prerequisite for us in primary care is that the radiologic determination of breast density is consistent and accurate. But, details, from an NIH supported study:

  • Data from 216,783 screening mammograms from 145,123 women aged 40 to 89 were included, from 30 radiology facilities within three breast cancer screening research centers of the Population-based Research Optimizing Screening through Personalized Regimens (PROSPR) consortium.
  • 83 radiologists were involved; each interpreted at least 500 screening mammograms from 2011-3, using the BIRADS reporting system, along with patients age, race, and BMI


  • 9% of mammograms were rated as showing dense breasts
  • Across radiologists, the finding of dense breasts ranged from 6.3% to 84.5% (median 38.7%, interquartile range 28.9% to 50.9%). !!!!
  • Variation in breast density assessment was pervasive in all but the most extreme patient age and BMI combinations
  • Among women with consecutive mammograms interpreted by different radiologists, 17.2% had discordant assessments of breast density.


  • One of the scariest issues to me as a clinician is that I need to rely on an accurate interpretation of medical tests in order to inform my patient management. The sheer magnitude of the variation in breast density assessment is quite striking.
  • There are also other studies, mostly 10-20 years old, showing that the general radiologic interpretation of mammograms has considerable variability as well.
  • There are certainly other tests that have significant variability andhighlight this issue more broadly — for example finding significant spine MRI abnormalities in totally asymptomatic patients:
    • One study (see Jensen MC. N Engl J Med 1994; 331: 69) looked at 98 people without back pain, where their MRI scans were interpreted by two experienced neuroradiologists at the Cleveland Clinic, finding that 52% had a bulge in at least one intervertebral disc, 27% had a protrusion, and 1% had an extrusion. 38% had multilevel abnormalities. Only 36% had a normal MRI.
    • A systematic review (see Brinjikji W. AJNR2015 36: 811-816) found dramatic MRI or CT changes in asymptomatic people, which increased with age.  For example, the prevalence of disc degeneration went from 37% at age 20 to 96% at age 80, bulges went from 30% at age 20 to 84% at age 80, disc protrusion from 29% age 20 to 43% at age 80, annular fissure from 19% age 20 to 29% at age 80.  so, lots and lots of impressive disc changes even in asymptomatic 20 year olds……
  • Another issue, which we tend to understand more intuitively, is that of ultrasounds, which are clearly operator-dependent. But we had a patient with chronic hepatitis B, who had a “normal” screening RUQ ultrasound for hepatocellular cancer, but a CT revealed a 9cm cancer!! I spoke with a trusted hepatologist who commented that he used a CT to scan to screen for really high-risk patients because of the variability of ultrasounds (though that is not exactly a clear-cut, or generally accepted algorithm….)
  • One major concern about over-reading breast density (as well as potentially scaring patients that they might be at higher breast cancer risk) is that this findingoften leads to further studies such as ultrasound, digital breast tomosynthesis, and MRI examination (though there is minimal evidence to support these tests, and they may well lead to unnecessary biopsies, more radiation exposure, etc. And the USPSTF formally gives these procedures an “I” rating, for insufficient evidence)
  • And, another issue:  half of the United States has legislation currently requiring disclosure of mammographic breast density, in some cases advising women to discuss supplemental screening tests with their providers if they have dense breasts (again without supportive medical evidence). And even theFDA is considering a legislative requirement to report breast density information to patients. I think there is a real concern about non-medical legislators enacting medical legislation, where legislators may be swayed by patients pleading for unproved treatments, perhaps with the support of an “expert witness”. Or, perhaps the legislature decides to require a certain treatment based on small or flawed studies, writes the treatment into law, but then new and better studies contradict this legislative imperative. One recent example is in Massachusetts, where a law was passed requiring insurance to cover long-term antibiotic therapy for chronic Lyme disease, though several studies, including a new one (see Berende . N Engl J Med2016;374:1209-1220), have not found benefit from long-term antibiotics. Or, in the past, there has been legislation supporting the availability of bone marrow transplants for women with breast cancer, but without any evidence of benefit (and pretty clear harm). I do realize that there have been egregious, inappropriate treatment denials by some health insurers in the past which has led to some of this legislation and public/medical community outrage. But legislating medical diagnostics and therapies is fraught…..
  • So, this inconsistency/unreliability in breast density interpretation may subject many people to potentially dangerous interventions. I think it is really important that we as clinicians understand that many procedures we order are subject to large variability, as above. So, what can we do??
    • Whenever possible, we should interpret these “objective” data in the context of the clinical situation of the patient, and not always reflexively respond to the test results (it is just another piece of data, such as from the history or physical, which should be put in the overall gestalt of what is going on with the patient). Of course, some of these objective findings, even unsuspected, may be very important and not dismissed (e.g., the incidental finding of early pancreatic or renal cancers).
    • Maybe we should consider getting second opinions more often than we currently do, to assess interobserver agreement
    • Perhaps there should be triggers in place for certain findings (such as dense breasts on mammogram), requiring a blinded read by another radiologist, or?? always having mammograms automatically re-read by another radiologist??, or having an automatic second-read whenever a radiologist comments “should be repeated in 3-6 months by another test”, which puts the medicolegal imperative on us in primary care to do yet another test with potentially more radiation exposure, cost, possible unnecessary procedures, etc.
    • Perhaps there needs to be much more transparency in the system overall, maybe requiring those reporting on these results to have regular standardized testing themselves and posting the results (sort of like requiring hospitals to report their C-section rates).
    • Perhaps we need a good computer program????
  • I realize this blog is more tangential than others, but i do think this issue of inconsistency in mammography reading does bring up a slew of general issues in clinical medicine…..

Primary Care Corner with Geoffrey Modest MD: Cervical Cancer Screening Less Frequently?

12 Oct, 16 | by EBM

By Dr. Geoffrey Modest

A recent review of cervical HPV screenings in the Netherlands found that those with negative screening could potentially be screened less frequently than every 5 years (see


  • 43,339 women aged 29-61 with a negative HPV and/or cytology were randomly assigned to HPV and cytology co-testing (intervention group) or cytology testing alone (control group); with 3 screens: at baseline, 5 years and 10 years; and with followup at 14 years. Those in the cytology only group also got HPV testing but this was blinded to all.
  • Mean age 43
  • Their triage approach (different from US recommendations):
    • For intervention group (cytology plus HPV):
      • Normal HPV and cytology: repeat in 5 years
      • At least moderate dyskaryosis on cytology: colposcopy
      • HPV positive, and neg or borderline/mild dyskaryosis (eg ASCUS or LGSIL) on cytology: repeat HPV/cytology at 6 and 18 months. refer to colposcopy if continued HPV positive or cytology worse
    • For control group (cytology only)
      • Normal cytology: cont routine screen
      • At least moderate dyskaryosis on cytology: colposcopy
      • Borderline/mild dyskaryosis (eg ASCUS or LGSIL) on cytology: repeat cytology at 6 and 18 months. refer to colposcopy if cytology same or worse


  • Co-testing group: 20,490 of 21,623 women had double negative HPV/cytology, 764 had pos HPV/neg cytology, 369 pos cytology/neg HPV
  • Cytology only group: 20,533 of 21,716 had negative cytology, 814 had pos HPV/neg cytology (the HPV results were blinded), 369 pos cytology/neg HPV
  • During 14 years of followup:
    • Co-testing: 149 CIN2, 152 CIN3 (including 5 adenoca in situ), 8 squamous cell and 6 adeno carcinomas
    • Cytology only: 126 CIN2, 169 CIN3 (including 5 adenoca in situ), 17 squamous cell and 10 adeno carcinomas
  • Breakdown of the 14 year followup according to cytology and HPV status (again, HPV results were blinded for the control group)
    • Cancer:
      • Cytology neg/HPV neg: 7 in intervention, 12 control; 3.3 vs 5.7/100,000 women, incidence ratio 0.58 (0.23-1.48), nonsignficant
      • Cytology neg/HPV pos: 4 in intervention, 15 control; 55.4 vs 190.9/100,000 women, incidence ratio 0.29 (0.10-0.87)
      • Cytology pos/HPV neg: 3 in intervention, 0 control; 79.7 vs 13.4/100,000 women, incidence ratio 5.97 (0.30-119.22), nonsignficant [but they had to use 0.5 instead of 0 for the cancer count, in order to do the math]
    • CIN3+ (the combination of cervical cancer and precancer):
      • Cytology neg/HPV neg: 74 in intervention, 86 control; 35.0 vs 40.7/100,000 women, incidence ratio 0.86 (0.63-1.17), nonsignficant
      • Cytology neg/HPV pos: 82 in intervention, 94 control; 1135.1 vs 1196.1/100,000 women, incidence ratio 0.95 (0.71-1.28), nonsignificant
      • Cytology pos/HPV neg: 10 in intervention, 16 control; 265.7 vs 427.1/100,000 women, incidence ratio 0.62 (0.28-1.37), nonsignficant
    • The cumulative incidence of cervical cancer 14 years after the initial negative cytology/negative HPV screen in the co-testing group (0.09%) was the same as in the cytology negative patients in the cytology-only group after 9 years
    • The cumulative incidence of CIN3+ was 0.56% 14 years after the initial negative/negative screen in the co-testing group, but 0.69% in the cytology negative patients in the cytology-only group after 9 years
    • Combining both groups, the incidence of CIN3+ was 72.1% lower (60.5-80.4%) in women >40 years old vs younger; no statistically significant difference in cervical cancer


  • Several studies have supported using only HPV screening without cytology (primary HPV screening) for detection of cervical dysplasia/cancer (g., see from BMJ or Ronco G. Lancet 2014; 383 (9916): 524); the latter study found that there was 60-70% better protection with primary HPV screening over cytology screening. And primary HPV screening might avoid over-referral to colposcopy and biopsies. And decrease the number of screens done/longer intervals between screenings. Several countries now do primary HPV screening including Australia, Italy, Netherlands, New Zealand, Sweden and the UK. The current study looked not just at cervical cancer, which may take years to manifest itself, but also to high-grade precancerous lesions (CIN3+) to try to ascertain if the longer screening interval could miss women with evolving cancers (which it didn’t: those with combined screening had the same incidence at 14 years as the cytology only group at 14 years).
  • So, this study suggests several things:
    • It confirms the superiority of HPV/cytology screening over cytology alone
    • The very low incidence of CIN3+ in the overall combined groups (including the blinded HPV testing of the cytology-only group) who had negative HPV testing (independent of cytology) was quite low: 84 events in 20,859 patients (e.g., as compared to those who were HPV positive but cytology negative, with CIN3+ in 82 of 764 patients), affirming that HPV testing is superior to cytology testing
    • The study also confirmed the utility of testing more than just the highest risk HPV 16/18 types, since there were 30 of 501 patients with CIN3+ who were HPV positive/cytology negative and HPV 16/18 negative
    • And the big conclusion was the very low risk of CIN3+ and cervical cancer itself in patients who were >40yo and had dually negative initial HPV/cytology
    • Putting this all together, in 2017 the Netherlands will implement the strategy of every 10-year screening for HPV negative women at least 40 years old
  • So, there really seems to be increasing data suggesting that primary HPV is a superior screening test (adding cytology seems to add more false positives than providing real clinical benefit), though i would imagine there need to be more studies in different populations to see what the optimal screening interval should be.

Primary Care Corner with Geoffrey Modest MD: Normal BMI/Exercise Lower Cancer Risk

23 Sep, 16 | by EBM

By Dr. Geoffrey Modest

The International Agency for Research on Cancer (IARC) working group just assessed the relationship between overweight/obesity and cancers, finding 8 more cancers associated with obesity (see Lauby-Secretan B. N Engl J Med 201; 375: 794). They relied on over 1000 epidemiological/observational studies to assess this association, since there really are no large randomized clinical intervention trials with long-term follow-up assessing the effects of weight-loss vs maintaining weight to see if there is a difference in cancer incidence.

  • Background, worldwide estimates:
    • In 2014: 640 million adults in 2014 (an increase by a factor of 6 since 1975) were obese
    • In 2013: 110 million children and adolescents (an increase by a factor of 2 since 1980) were obese
    • In 2014: prevalence of obesity was 10.8% among men, 14.9% among women, and 5.0% among children; and globally more people are overweight or obese than are underweight.
    • In 2013: 4.5 million deaths worldwide were caused by overweight and obesity; the obesity-related cancer burden represents up to 9% of the cancer burden among women in North America, Europe, and the Middle East.
    • In 2012: 1 million new cancer cases and 8.2 million cancer-related deaths
  • The 8 new cancer associations:
    • Colon or rectum, RR = 1.3, with positive dose response relationships (e., the more overweight, the higher the risk)
    • Gastric cardia, RR = 1.8, with positive dose response relationships
    • Liver, RR = 1.8, with positive dose response relationships
    • Gallbladder, RR = 1.3, with positive dose response relationships (though in their analysis, comparing the top vs bottom decile of activity, this achieved a P=0.06 only)
    • Pancreas, RR = 1.5, with positive dose response relationships
    • Kidney, RR = 1.8, with positive dose response relationships
    • Esophageal adenocarcinoma, RR=8, with positive dose response relationships
  • In general the relative risks increased from 1.2 to 1.5 for overweight and from 1.5 to 1.8 for obesity for cancers of the colon, gastric cardia, liver, gallbladder, pancreas and kidney
  • These results were consistent in different geographic regions, and were similar for men and women
  • The previously known cancers with associations:
    • Breast cancer in postmenopausal women, RR of 1.1 per 5 BMI units, esp in estrogen-receptor positive tumors
    • Endometrial cancer: RR=1.5 for overweight,5 for BMI 30-35, 4.5 for BMI 35-40, and 7.1 for BMI>40
    • Ovarian cancer (epithelial): RR=1.1
    • Multiple myeloma, RR=1.2 for overweight, 1.2 for BMI 30-35, 1.5 for BMI 35-40, and 1.5 for BMI>40
    • Meningioma, RR = 1.5
    • Thyroid, RR=1.1
  • And there is some limited evidence of an obesity association with male breast cancer, fatal prostate cancer, and diffuse large B-cell lymphoma
  • For breast cancer, there was an association between increased BMI at the time of diagnosis and reduced survival
  • In terms of weight loss: the quality of the data are not great, but there are some suggestions that weight loss (including by bariatric surgery) may reduce the breast and endometrial cancer risks.
  • As supporting evidence:
    • Animal data (different animals) confirm an association between obesity and cancer at many different sites
    • Animal data also supports the effect of limiting weight gain vs food ad libitum for some cancers (mammary gland, colon, liver, pancreas, skin, pituitary) but inverse relationship with others (prostate, lymphoma, leukemia)


  • As with all of these observational studies, association does not imply causality. For example, is it the obesity itself which is associated with cancer? Or, are there specific things that obese people do differently than normal weight ones (e.g., eating certain oncogenic foods? not exercising enough? living in more toxic environments?)
  • The above results were similar for BMI and waist circumference when that data was available (waist circumference has a higher correlation with visceral obesity, which is the metabolically more active obesity associated with metabolic syndrome, increased inflammatory markers, )
  • In many of the above associations, the associations persisted in studies using mendelian randomization (see , which describes mendelian randomization and some of its limitations, but overall it is a process that assesses known genetic markers for a disease to help assess causality (to differentiate in this case whether the causality is if those genetically predisposed to obesity are more likely to get the cancer, not vice-versa or as independent phenomena)
  • Possible mechanisms: increased body fat is associated with multiple metabolic and endocrine changes (sex hormones, insulin and insulin-like growth factor, inflammation), which could promote tumor initiation and/or growth
  • It is important to keep in mind the strength of the associations above. Typically, in observational studies, a relative risk of under 1.5-2 often does not pan out as being really significant, despite the fact that it can be really significant in randomized controlled trials. So, a bit of a caution in over interpreting the above results for many of the cancers. The dose-response relationship does add some support the associations, however.


Another recent article came out on the relationship between physical activity and cancer (see doi:10.1001/jamainternmed.2016), finding that leisure-time physical activity was associated with lower risk of many cancers. Details:

  • 12 prospective US and European cohorts with self-reported physical activity from 1987-2004, including 1.44 million participants, looking at 26 different cancers
  • Mean age 59 (19-98), 57% female, mean follow-up 11 years (7-21), mean BMI 26, 54% ever-smokers
  • 186,932 cancers diagnosed
  • Leisure-time activity, defined as high if 6 or more METs. Median activity was 8 MET-h/week (equivalent to 150 minutes of moderate-intensity exercise, e.g. walking)
  • Results:
    • High vs low leisure-time activity was associated with lower risk of:
      • Esophageal adenocarcinoma (HR 0.58, i.e., 42% decreased risk)
      • Liver cancer (HR 0.73)
      • Lung cancer (HR 0.74)
      • Gastric cardia (HR 0.78)
      • Endometrial (HR 0.79)
      • Myeloid leukemia (HR 0.80)
      • Myeloma (HR 0.83)
      • Colon (HR 0.84)
      • Head and neck (HR 0.85)
      • Rectal (HR 0.87)
      • Bladder (HR 0.87)
      • Breast (HR 0.90)
    • In aggregate, there was a 7% lower risk of total cancer in those performing higher levels of physical activity [HR 0.93 (0.90-0.95)]
    • Adjusting for BMI (nullied the relationship above for liver, gastric cardia and endometrium) but otherwise only a small attenuation of the risk, on the order of 5-11% of the HR’s. Smoking status affected lung cancer but not the others
    • Some cancers were associated with more activity
      • Melanoma (HR 1.27)
      • Prostate cancer (HR 1.05)


  • One striking finding is the overlap of cancers which seem to be affected by both BMI and exercise, reinforcing that these lifestyle/environmental issues seem to be particularly important.
  • But, one needs to be particularly careful in meta-analyses in general and huge ones in particular: it is very hard to get granular data over time (what is “ever-smokers”? a few cigarettes at the beginning of the study? stopping smoking 2 packs/day near the end of the study?); how often did they track information, such as changes in BMI or physical activity over time? Was it just a one-shot assessment at the beginning of the study? And how did they then quantitate these typically changing variables over such a long follow-up?  This data acquisition is done differently in different studies, so how is this all put together mathematically? It is pretty striking the range of ages (19-98) and years of follow-up (7-21) in the individual studies, suggesting they were pretty heterogeneous. And, in general, the people in this large meta-analysis were reasonably lean (BMI=26), so it may be difficult to really control for BMI in their data (they divided the patients into BMI <25 vs >25, but did not have the BMI spread of the IARC study). This limits the interpretation of their finding in this exercise study that 3 of the highest risk cancers in the AIRC study for BMI had no relationship to exercise when controlling for BMI.
  • They only looked at leisure-time physical activity. It seems pretty intuitive that people with very physical jobs do have more exercise at work than those with office jobs (i.e., many of my patients are on their feet all day, walking around cleaning office buildings, etc. And it seems they should get some “exercise” credit for that.) There are not great studies which have looked at occupationally-related exercise, probably because it is hard to measure on an individual basis: even those with the same job category may have very different amounts of exercise if they clean a small office vs a large automated office building)
  • One concern is that the burden of obesity and lack of exercise is increasing, especially with migration to larger cities and with increasing Westernization around the world
  • But one potentially positive finding is that exercise is associated with lower cancer risk independent of BMI for many cancers (with above caveat): it is much easier to help people do exercise than to achieve sustained weight loss (see ). And there are reasonable postulated mechanisms by which exercise could decrease cancer: hormonal changes (sex steroids, insulin and insulin-like growth factos, adipokines; similar to the BMI mechanisms postulated above) as well as nonhormonal (decrease inflammation, improve immune function/surveillance, decrease oxidative stress, and increase GI transit time, the latter of which could decrease colon cancer incidence)
  • There are still many questions, even if one accepts the conclusions of these studies
    • Does instituting a more aggressive exercise program lead to decreased cancer (i.e., an intervention study would provide stronger conclusions than an observational study)
    • And how much exercise works? Is there a threshold? Is it different for different cancers? (this might be important in different parts of the world where different cancers predominate)
  • But, the real bottom line is that there have been many studies over the years showing that lifestyle/environment are associated with pretty much all of the chronic diseases in the world. The above studies simply reinforce the association with cancer. And it offers us as clinicians yet another way to talk with patients about the importance of a healthy lifestyle. The association with cancer may be a particularly useful tool in motivating patients to avoid progressing to a less healthy lifestyle over time or instituting changes to improve their lifestyle (for better or worse, patients given equal mortality scenarios from cancer or heart disease, for example, are more afraid of the cancer one…it just sounds scarier)

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