New method for expressing survival in cancerBMJ 1997; 315 doi: https://doi.org/10.1136/bmj.315.7119.1375 (Published 22 November 1997) Cite this as: BMJ 1997;315:1375
*We also received five other letters commenting on this article. They appear (unedited) on our web page.—Editor
Use of percentage of “normal remaining life” may be confusing
- L B Tan, BHF/Mautner senior lecturer in cardiovascular studiesa
- a Regional Cardiothoracic Centre, Killingbeck Hospital, Leeds LS14 6UQ
- b Liverpool University Dental Hospital, Liverpool L3 5PS
- c Istituto Nazionale per lo Studio e la Cura dei Tumori, Division of Medical Statistics and Biometry, Via G Venezian 1, I-20133 Milan, Italy
- d Istituto Nazionale per lo Studio e la Cura dei Tumori, Division of Medical Statistics and Biometry, Via G Venezian 1, I-20133 Milan, Italy
Editor—Jayant S Vaidya and Indraneel Mittra propose a new way of presenting survival data in patients with cancer, which may also be applicable to other diseases.1 However, several issues need to be considered before this new method is adopted for widespread use.
A common misconception that patients have about life expectancy (for example, 75 years at birth for male infants in Britain) is that they would not be expected to survive beyond the stated number of years. Some may even rationalise to themselves that once they reach the age of 75 their “time is up.” Clarification of every new term or concept introduced to the patient is necessary to avoid misunderstanding and subsequent distress.
When one states that the life expectancy is, for instance, 15 years at the age of 60, this figure represents the median survival for that population cohort. In other words, if the survival curve is plotted for this cohort as a “real life expectancy curve” (as, for example, in figure 2 in the authors' paper), the percentage survival at “full” term of the “normal remaining life” would be 50%. Thus, in the authors' figure 2, the 68% survival to full “normal remaining life” in their cohort of patients with breast cancer who were node negative suggests not only cure but also a better survival rate than that of the general Indian population. Does this imply that the actuarial data from the Life Insurance Corporation of India was unrepresentative or, alternatively, that the disease process …
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