Tuesday, December 21, 2010


One day you read in the paper or hear on TV that being overweight will cause you to die earlier. The following week you hear just the opposite. So what should you believe? Well, it is not easy unless you read the original epidemiological literature and analyze the results yourself.

But, you don’t have to do that because I have already done it.

Recently I posted a blog concerning body weight and death in which I summarized two recent studies which showed that bodyweight and death were related by a U-shaped curve (shown below). That is, if you are too skinny or too fat (obese) you are at a greater risk of death and that just being overweight did not increase the risk.

The data shown in the figure below was taken form McGee DL (2005) Ann Epidemiol 15:87 and Adams KF (2006) N Engl J Med 355:763


As you can see, if you weight too much or too little your risk of death is increased by approximately 1 to 2 percent as compared with the normal weight people. The group numbers indicate bodyweight category: 1. Underweight, 2-4. Normal weight, 5-7 Overweight and 8-10 Obese. These data are for men but the data for women are very similar.

It is clear from these data that people in the overweight groups of 5-7 are not at any greater risk of death than the normal weight groups 3-4. But there is a greater risk for being underweight (groups 1 and 2) or obese (groups 9 and 10).


Now a new study says that both overweight and obese people are at greater risk of death (de Gonzalez et al 2010 N Engl J Med 363 2211). So what should you believe?

As noted above, in the field of epidemiology, which is where all of these kinds of studies come from, disagreement almost always exists. In the case of bodyweight and death the disagreement level is greater than usual and downright ridiculous. For example:





So if the data and conclusions are so contradictory why go on? Why not just accept that the fact that the truth about fat and death will never be clear? Because very recently a paper was published which claims it has uncovered the truth and all other studies should be ignored (de Gonzalez et al 2010 N Engl J Med 363 2211). Right off the bat you realize, it can’t be true, so what is the real story.

This group has combined a large study which made up of 57 other studies (Prospective Studies Collaboration 2009 Lancet 373 1083) and added four more in order to come up with their own set of data from which they conclude that being overweight or obese will cause you to kick off sooner.

However, The Prospective Study showed the same U-shaped curve as we have already discussed. The only difference is that more groups were added in the Obese Category which made the curve slightly J-shaped. The values for Normal Weight average 9.6/yearly deaths /1000 and 9.8/yearly deaths/1000 for the Overweight group. Clearly not different. Hence being overweight poses no addition risk of death. The real skinny and obese groups were at a greater risk of early death but the overweight were not.

The deGonzalez group has taken the above data and combined it with four other studies and the combination was analyzed. Of the four studies listed two had no useable data and the other two are discussed below.

One of these by Hu et al (2004 N Engl J Med 351 2694) shows a linear trend of increase risk of death as a function of body mass index.

This is an example of an upward linear relationship and does not agree with most other studies. However the inclusion of these data in the de Gonzalez study decreases the upward curve of the underweight people and makes it appear that if there is a risk in this group it is very low. Notice that the difference between normal weight (2-3) and overweight (4-6) is 0.51-0.34= 0.17% which is not significant.

The study by Baik et al (2000 Am J Epidemiol 152 264) indicates that underweight people are at somewhat greater risk of death and that normal weight and overweight people are have no significant increase in risk. Whereas obese people are at somewhat greater risk.

Curiously, the study by Klenk et al (2009 Eur J Epidemiol 24 83) was not added to the list. Could it be because the data in Klenk et al 2009 show a U-shaped curve with conclusions about overweight people similar to those discussed above and obtained from McGee 2005 and Adams 2006.

In their final analysis de Gonzalez et al conclude that overweight and obese people are at greater risk of death. However, the small differences between overweight and normal groups are very small and of no biological significance. The authors are able to claim statistical significance because the number of subjects is so large. Thus many studies (some good, some poor, and some bad) many of which are not statistically significant can be brought together and suddenly statistical significance pops out. It is my opinion and the opinion of many others that such lumping of diverse studies into one analysis is a crock of statistical crap.

Obviously I believe that the U-shaped curve holds and overweight people are not at any greater risk of death than normal weight people.

Saturday, December 18, 2010


By James H. Clark

The following is a short summary of my paper which explains why postmenopausal hormones do not cause breast cancer, but instead, increase the level of detection which is a good thing.

Almost all of the studies published concerning postmenopausal hormone replacement therapy (HRT) use the phrase: The risk of breast cancer was increased as a result of HRT. The implication is that during the study HRT caused the cancer to form and grow to a size which could be seen by mammographic screening. This is very unlikely because breast cancers require from 10 to 20 years or more to reach a size that is detectable. Since studies of HRT are usually 5 years or shorter it would be impossible to observe a hormone initiated cancer.

So what are these scientists observing? They are detecting hidden tumors. In some women breast tumors exist in a hidden state (occult) and are not big enough to be detected. However, since some of these tumors are hormone sensitive they grow from the occult size to a size which can be detected by screening and are mistakenly labeled hormone induced cancer.

So every time you read in the paper that some HRT increases the risk of breast cancer, just substitute detection for risk. HRT is not causing breast cancer it is just detecting hidden cancers which can be a good thing.

The following paper explains in more detail the summary points made above.


By James H. Clark

Most papers published on the relationship between estrogen and progestin replacement therapy (EPHRT) of postmenopausal women indicate that such treatment increases slightly the risk of breast cancer. The implication being that these hormones cause breast cancer. Although these results have been discounted by several investigators, their conclusions continued to be quoted as fact in the scientific, news and television media. The purpose of this paper is to show that such studies cannot claim that EPHRT increases the risk of breast cancer. Instead what they have been studying is the small increases in the growth of preexisting cancers which were too small to be detected at the beginning of the studies. Therefore, the only claim they can make is the EPHRT may increase the detection of occult cancers and this may be a good thing.


The length of most EPHRT studies is too short for an increased incidence of BC to be detected if EPHRT were the cause of this increase. This is true because the time between initiation of breast cancer and the time that cancer can be detected varies between 10 to 20 years (Dietel et al. 2005; von Fournier et al. 1980; Koscielny et al. 1985). Since most EPHRT studies are between 5 and 10 yrs any tumor that was initiated by hormone treatment would not be apparent for at least 10 yrs and probably more.

As pointed out by Dietel et al (2005) these estimates of time between inception and detection are based on calculations of tumor doubling time (TDT) which has been reported to be between 23 and 209 days (Spratt et al., 1977; Shackney et al., 1978; Spratt and Spratt, 1985; Haskell, 1985). All things considered the average TDT is considered to be 50-100 days (Spratt et al., 1995). Since a mammary tumor cannot be detected until it reaches approximately 1 cm and would contain approximately 10 billion cells, the time to produce this number of cells would be between 5 and 10 years. This time period is an underestimate because the loss of cells due to apoptosis and the length of the carcinoma in situ, which is very variable and can be several years, are not taken into consideration.


Most studies of EHRT have shown no increased detection of breast canceer and some have shown a decrease. In contrast, EPHRT studies consistently show a small or marginal increase in detection of breast cancer. This probably occurs as a result of estrogen plus progesterone stimulating the more highly differentiated occult cancers which contain receptors for these two hormones. Progesterone appears to have angiogenic effects which may be the cause of an additional effect on growth which is not seen with estrogen alone (Liang 2007 Cancer Res 67 9929; 32: Hyder 1998 Cancer Res 58 392). Whereas, estrogen only exposure may not produce a significant growth response because the tumor is less well differentiated and is incapable of a growth response.


Increased detection as a result of EPHRT means that tumors could be treated sooner and this potentially could reduce morality. This may be the case since these tumors have favorable characteristics which are associated with decreased mortality. Many investigators have found a such characteristics associated with decreased mortality (Kerlinkowske 2003; Newcomb et al 2008)

The increased detection could be due to more frequent screening of women who use HRT than nonusers. However even in studies which adjust for screening bias the tumors HRT tend to be smaller ( Bonnier 1995; Magnusson 1996) of lower grade ( Harding 1996), less advanced stage (Holli 1998; Christante 2008) have fewer positive axillary lymph nodes (Bonnier 1995; Magnusson 1996, Hardin 1996; Squitieeri 1994), lower tumor cell proliferation rate (Oestreicher 2004; Holli 1998, and have other clinically more favorable features (Schnitt 2001; Holli 1998; Chen 2004; Rosenberg 2008; Newcomb 2008).

In contrast to the above studies Chlebowski 2010 found that mortality was increased by EPHRT in the WHI studies. The WHI authors explain that other studies are not as valid as those of the WHI because they were not randomized placebo controlled trials. However it is difficult to disregard the many studies which do not agree with WHI especially since some of them are just as valid, if not more so, than those of the WHI. The WHI studies were far from perfect and have been criticized at length by many scientists.

For instance: Many investigators agree that the WHI study does not even qualify as a randomized placebo-controlled study which is supposed to be superior to other types of studies. The reasons for this statement are: 1. Following randomization the women were free to decide whether to continue their assigned treatment or whether to undergo diagnostic procedures. 2. Almost half of the women were aware of their treatment so there was no valid placebo group. 3. Several warnings were sent to the participants about the detection of increased risks of myocardial infarction, stroke and pulmonary embolism during the study. These problems make the WHI study no better than any observational study with all of their limitations (Clark JH 2006).


Following the release of the WHI results in 2002 there was a decline in the number of detected breast cancers which was associated with a decrease in the number of women taking EPRT. Many investigators have taken this as evidence that EPRT causes breast cancer. However, it is much more likely that the decreased number of breast cancer was due to a decreased detection of occult tumors which would have been observed if EPRT had continued.

As Berry and Ravdin (2007) explained: If EPRT caused breast cancer and millions of women stopped taking EPRT there would be a long slow decline in the number of breast cancers, not a rapid decline between 2002 and 2003 as has been reported. Breast cancer has a long preclinical period that varies in duration from one tumor to another. So a drop in breast cancer incidence would be gradual and not discernable for several years after EPRT was stopped.

A more likely possibility is that a cessation of EPRT removes the hormonal stimulation of receptor positive cancers and their growth rate decreases. If this were the case a discernable and rapid drop in breast cancer numbers would be observed. To use a modified example from Berry and Ravidin (2007): Consider 30 to 40/100,000 women with receptor positive cancers that were growing and destined to be detected in 2003. They had negative mammograms in 2002 and then when the WHI results were announced they stopped taking EPRT. Without the hormonal stimulation their cancers stopped growing and were not detected by the mammograms in 2003. So the overall decrease on breast cancer incidence rates would be immediate and noticeable. This seems to be the case since the rate of decline of breast cancers was rapid between 2002 and 2003 and was parallel to receptor positive cancers (Ravdin 2007).


The preponderance of evidence indicates that EPHRT stimulates some occult breast cancers to grow to a size which is detectable by screening. Such tumors were not caused by the hormonal exposure because the length of time of most studies is too short for tumors to grow to a detectable size. Therefore these hormone responsive tumors are being detected before they would be in nonusers of hormone therapy. This appears to be a good thing since these tumors have favorable characteristics and are associated with a decreased rate of mortality.


The Endocrine Society just published a 65 page review of HRT which agrees and substantiates my views (Santen 2010 J Clin Endocrinol Metabol 95 S1-S66).


Berry DA, Ravdin PM (2007) Breast cancer trials: A marriage between clinical trial evidence and epidemiology. JNCI 99: 1139-1141

Bonnier et al.(1995) Clinical and biologic prognostic factors in breast cancer diagnosed during postmenopausal hormone replacement therapy. Obstet Gynecol 85:11–7

Chen et al (2004) Association of hormone replacement therapy to estrogen and progesterone receptor status in invaseive breast carcinoma. Cancer 101 1490

Chlebowski et al 2010 Estrogen Plus Progestin and Breast Cancer Incidence and Mortality in Postmenopausal Women. JAMA 304 1684

Clark (2006) A critique of the Women’s Health Initiative Studies: estrogen plus progestin (Prempro). Nuclear Receptor Signaling 4, e023

Dietel et al. (2005) Hormone replacement therapy: pathobiological aspects of hormone-sensitive cancers in women relevant to epidemiological studies on HRT: a mini-review. Human Reproduction 20:2052-2060.

Harding et al.(1996) Hormone replacement therapy and tumour grade in breast cancer: prospective study in screening unit. BMJ 312:1646–7.

Haskell CM (1985) Thorax, Unknown Primary—Breast Cancer in Cancer Treatment, 2nd edn. WB Saunders Company

Holli (1998) Low biologic aggressiveness in breast cancer in women using hormone replacement therapy. Clin Oncol 16(9):3115-20.

Hyder et al.(1998) Progestin regulation of vascular endothelial growth factor in human breast cancer cells. Cancer Res 58 392

Kerlikowske et al. (2003) Prognostic characteristics of breast cancer among postmenopausal hormone users in a screened population. J Clin Oncol 21:4314–21.

Koscielny S (1985) A simulation model of the natural history of human breast cancer. Br J Cancer 52:515-524.

Liang et al. (2007) Progestin dependent progression of human breast tumor xenograpfts : a novel model for evaluating antitumor therapeutics. Cancer Res 67 9929

Oestreiche (2004) Hormonal factors and breast tumor proliferation: do factors that affect cancer risk also affect tumor growth? Breast Cancer Res Treat 85:133–42

O'Meara (2001) Hormone replacement therapy after a diagnosis of breast cancer in relation to recurrence and mortality. J Natl Cancer Inst 93:754–61.

Ravdin (2007) et al. The decrease in breast-cancer incidence in 2003 in the United States . NEngl J Med 356 : 1670 – 4 .

Schuetz (2007) Reduced incidence of distant metastases and lower mortality in 1072 patients with breast cancer with a history of hormone replacement therapy. Am J Obstet Gynecol. 196(4):342.e1-9.

Sener (2009) The effects of hormone replacement therapy on postmenopausal breast cancer biology and survival. Am J Surg. 197(3):403-7.

Schnitt (2001) Traditional and newer pathologic factors. J Natl Cancer Inst Monogr 30:22–6.

Shackney et al.(1978) Growth rate patterns of solid tumors and their relation to responsiveness to therapy: an analytical review. Ann Intern Med 89, 107–121.

Spratt JS and Spratt JA (1985) What is breast cancer doing before we can detect it? J Surg Oncol 30, 156–160.

Spratt (1977) Cytokinetic definition of acute and chronic breast cancer. Cancer Res 37, 226–230.

Spratt et al (1995) Rates of growth of human solid neoplasms: part I. J Surg Oncol 60, 137–146.

Squitieri et al. (1994) Carcinoma of the breast in postmenopausal hormone user and nonuser control groups. J Am Coll Surg 178:167–70.

Rosenberg et al. (2008) Menopausal hormone therapy in relation to breast cancer characteristics and prognosis: a cohort study. Breast Cancer Research 10;R78 (doi:10.1186/bcr2145)

Newcomb et al (2008) Prediagonistic use of hormone therapy and mortality after breast cancer. Canceer Epidemiol Biomaarkers Prev 17:864-871.

von Fournier et al. (1980)Growth rate of 147 mammary carcinomas. Cancer 45:2198-2207.