Despite detailed reports on the epidemiology of cancer published by registries they hardlyever mention hazard rates. Which is unfortunate since hazard rates reveal more cancer biology than any survival curve. Observe the next curve depicting breast cancer observed survival

Data source: Surveillance, Epidemiology, and End Results (SEER) Program ( SEER*Stat Database: Incidence - SEER 9 Regs Public-Use, Nov 2004 Sub (1973-2002), National Cancer Institute, DCCPS, Surveillance Research Program, Cancer Statistics Branch, released April 2005, based on the November 2004 submission.

Itobviously declines, yet what is less obvious how it declines! From the third year and onward the slope of the curve continually declines. In other words, the magnitude of this decline declines with time. This cumbersome sentence means that breast cancer hazard rate declines. In other words, the longer a patient lives the better her chances to survive! Yet this optimistic message may be deduced solely from hazard rates,

Bi-modal hazard BMH

The survival curve smooths out variation and hides a pattern of great consequence. The hazard rate is bi-modal. Initially it rises then declines to rise again. This pattern is called here bi-modal hazard (BMH). It is unique to cancer and does not appear in other chronic diseases. It is an epidemiological hallmark of cancer. It is so typical of cancer that it distinguishes cancer from other chronic diseases.

Cancer proceeds through two phases, compensated, when the tumor does not cause any damage or distress, and de-compensated, when the patient suffers. BMH is more pronounced in compensated cancer. The earlier cancer is detected the more distinct is BMH. In breast cancer it is most pronounced and far less distinct in lung cancer since when detected it is decompensated.

Some of the hazard rate estimates smooth out variation and obscure BMH. The present studies apply hazard rate fractions:
HR = #died / (#live at start of the interval - #lost to follow up)

BMH has other epidemiological manifestations:

1. The relapse rate following breast cancer surgery is bi-modal. (Retsky et al.(1)).
2. The hazard rate of the first breast cancer recurrence is bi-modal (Karrison et al (2).
3. Annual hazard rates of recurrence for breast cancer after primary therapy are bi-modal (Saphner et al (3))
4. Mammography paradox: The hazard following mammography of young females is higher than in controls Cox (4).
5. Hazard rates of recurrence following diagnosis of primary breast cancer Jatoi et al. (5)
6. Hazard rate of recurrence of breast cancer in 3811 spanish patients.
7. BMH is pronounced after radiation which destroys the tumor more efficiently than other treatments.
7a Genital cancers
7b Lung cancer

-- These epidemiological manifestations of breast cancer originate in one and the same phenomenon: BMH
-- They are linked to cancer detection and treatment. They indicate a potential iatrogenesis.
-- Since bi-modal hazard rates appear in other cancers, e.g. colon, skin melanoma and prostate this phenomenon is common to all cancers. In other words it is an epidemiological phenomenon unique to cancer.
-- In cancers that are diagnosed relatively late, e.g., lung cancer, the ascending portion of BMH is missing and their hazard rate declines.

The descending portion of BMH appears in all cancers and does not appear in other chronic diseases.

Medical significance of BMH (portrayed in the above figure)

1. AB segment: Hazard rises due to treatment.
2. BC segment: The declining hazard indicates that with time the patient resists cancer better and better. The longer she lives the better her chances to survive. The nature of this resistance is the major concern of this web-site. Although treatment also contributes to this decline, it appears in untreated breast cancer and in patients who were treated only once and not treated again later on
3. CD segment: Marks the final decline when resources are depleted and illness overpowers the patient.


These observations convinced me to propose the following hypothesis.

Cancer is a metabolic deficiency caused by a deficiency of a yet unknown metabolite A. In order to replenish the missing metabolite the organism grows a tumor which produces a substitute B. Since the deficiency continually aggravates, the tumor has to grow more and more in order to replenish the missing metabolite. In advanced deficiency tumor destroys vital functions and finally kills the patient. Tumor ablation aggravates the deficiency and the hazard rises. Patients with micro metastases are protected from therapy induced total ablation and their hazard rate declines.

Clinically this deficiency is manifested by a wasting disease which starts with weight loss and gradually turns into overt cachexia It is named here pernicious cachexia. The tumor protects against cachexia.

Treatment objectives: Do not treat unless the tumor causes pain and distress or destroys vital functions. Wait as long as cancer is compensated and treat only during decompensation.

Some detailed studies:
1. Tumor ablation in compensated breast cancer raises its hazard rate.
2. This phenomenon is observed also in other cancers and in prostate cancer
3. Bi-modal hazard rate in untreated breast cancer
4. A simple model of breast cancer 4a A Gompertz model of bi-modal hazard rates
5. Relapse rate following surgery. 5a A simple model of relapse rate
6. Treatment promotes cancer progression
7. Conditional Survival
8. Tumor dependency
9. Radiation induced hazard in genital cancers
10. Radiation induced hazard in lung cancer
11.In advanced age cancers progression is slower than in young patients.
12.Despite rising breast cancer age adjusted incidence rate its biology did not change.
13. Long survival with micrometastasis

Farewell my breast


1. M. Retsky, R. Demicheli and W. J.M. Hrushesky
Does surgery induce angiogenesis in breast cancer? Indirect evidence from relapse pattern and mammography paradox  International Journal of Surgery  Volume 3, Issue 3
, 2005, Pages 179-187
2. Karrison TG,. Ferguson DJ, Meier P. Dormancy of mammary carcinoma after mastectomy
J. National Cancer Institute, (1999) 91 : 80-85.
3. Saphner T, Tormey DC, Gray R. Annual hazard rates of recurrence for breast cancer after primary therapy
J Clin Oncol 1996; 14: 2738-2746.
4. Cox B, Variation in the effectiveness of breast screening by year of follow-up, J Natl Cancer Inst Monogr 22 (1997), pp. 6972
5. Ismail Jatoi , Anna Tsimelzon , Heidi Weiss , Gary M. Clark and Susan G. Hilsenbeck
Hazard rates of recurrence following diagnosis of primary breast cancer
Breast Cancer Research and Treatment 2005; 89: 2; 173-178

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