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Predictive power

Modified BMI formulas help predict cancer risk

Lung carcinoma. Modifying the BMI formula can increase its predictive power in predicting lung cancer risk for non-smokers. Photo: Flickr / euthman
Lower values for x in kg/m(x) affect power of BMI in predicting cancer risk
Results suggest possibility of a range of scaling for BMI for different uses

Modifying the formula used to calculate BMI can make it more accurate as a predictor of different forms of cancer, according to a new study in the American Journal of Epidemiology.

The authors say that lowering the value by which the patient’s height is multiplied makes it a more powerful predictor of cancer risks, including endometrial cancer, lung cancer in non-smokers, and post-menopausal breast cancer.

Noting that BMI has long been known to be an imperfect measurement of an individual’s weight, lead author Geoffrey Kabat, senior epidemiologist in the department of epidemiology & population health at Yeshiva University, said: “when using weight and height data, a single BMI formula may not be appropriate for all populations and all diseases.”

BMI is calculated by taking a person’s weight in kilograms and dividing it by their height in metres raised to the power of two, normally written as kg/m2. However, the researchers for this paper examined how modifying the power that the individual’s height is raised by – the x in kg/mx – influenced its association with the risk of 19 different kinds of cancer.

While they investigated figures for x from 0 to 3.0, in increments of 0.1, they found that the predictive power of the formula always dropped when x was increased above 2.

The formula Kabat et al found that the following formulas produced the most statistically significant hazard ratios for different kinds of cancer:

  • kg/m0.8 for endometrial cancer;
  • kg.m1.3 for lung cancer in individuals that have never smoked, and
  • kg/m1.7 for postmenopausal breat cancer.

The study used data from the Canadian National Breast Cancer Screening Study, which included 89,835 women screened for breast cancer between 1980-2000.

The authors concluded that their results “suggest that the scaling of weight for height may vary depending on the cancer site and that optimal scaling may be considerably different from kg/m2 or, alternatively, that a range of scaling should be considered when examining the association of body weight with risk of disease.”

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