We present a model that predicts the probability or absolute risk of developing CRC for men and women age 50 years and older. We combined separate RRs and ARs and baseline hazards for proximal, distal, and rectal cancers to project the risk of the earliest of these tumors. We also developed a short, simple, self-administered risk assessment questionnaire that can be used to obtain information for risk estimation.
In related work, we used independent data from the National Institutes of Health (NIH)-AARP Diet and Health Cohort Study26
of men and women age 55 years and older to assess the performance of our models.27
We found that the models had discriminatory accuracy comparable with absolute risk models for other cancers and were well calibrated.
Although the models were developed from cases and controls age 50 years and older, one could project risk for younger individuals by assuming that our relative and ARs apply to younger populations and by using younger age-specific SEER rates. However, such assumptions would need to be checked in independent data because risk factors and biologic mechanisms may differ among those developing CRC at younger ages.
Although absolute risk models exist for breast cancer and lung cancer,19,28
this is the first such model for CRC. The four other CRC risk prediction models currently available either apply to special populations, such as patients who were referred by general practitioners to gastroenterologists for symptoms,8
provide a qualitative index of CRC risk,7,10
or predict different outcomes, such as the risk of having an advanced polyp or cancer in the proximal portion of the colon.9
Our model estimates the probability of developing CRC over a prespecified time interval from data collected from two large US population-based case-control studies of colon and rectal cancer, incidence data from 13 SEER registries, which are generally representative of the US population29
and from national mortality rates. Thus, our risk prediction models would be expected to apply to the general non-Hispanic white US population.
We used factors in our models that, in addition to having strong predictive ability, can also be ascertained easily in a clinical setting. Thus, we did not include some factors that may have predictive value, such as and calcium intake or long-term vigorous activity30–33
but which would require a much more complex questionnaire.34
Our risk prediction model has some limitations. Because the majority of participants in the case-control studies were white, we could not estimate RRs for other racial or ethnic groups. A first step to developing models for other racial/ethnic groups could be to combine RR and AR estimates for whites with SEER rates for blacks, Asians, or Hispanics. However, the assumption of constant AR and RR estimates across racial groups needs to be validated in minority populations. Our model is not applicable to individuals with ulcerative colitis, Crohn's disease and familial adenomatous polyposis, because these conditions carry a high risk of CRC, and individuals with these conditions were excluded from the studies. Additionally, our model is not applicable to individuals with hereditary nonpolyposis CRC.
Because we used US mortality data from 1990 to 2002 for our competing mortality hazards, we did not adjust these estimates for potential confounders such as BMI given that our sensitivity analyses indicated that changes in the risk estimates were small (data not shown). Although our two case-control studies were conducted at slightly different time periods, we believe any changes in the distribution of risk factors would have a minimal effect on our risk estimates, considering that RRs and ARs were estimated separately for the two studies.
Another limitation of our model is that we estimated our RRs and ARs from case-control rather than from cohort studies. Although case-control studies have been used in the development of risk prediction models for melanoma,35
and lung cancer,39
a general criticism is that such estimates could be subject to recall bias. However, recall bias likely plays a minor role in our models as most of the RRs we found, including BMI, physical activity, HRT, and aspirin and NSAIDs use, were consistent with RRs summarized in a recent comprehensive review of the epidemiologic literature.6
Although not covered in this review, our risk estimates for screening and polyp history,2,40,41
and family history43,44
are also consistent with many previously published findings, including results from cohort studies. Additionally, the models were well calibrated in an independent validation study using the AARP cohort.27
In summary, we developed an absolute CRC risk projection model for white men and women age 50 years or older that may aid physicians and their patients in deciding on screening regimens, and can also be useful in designing chemoprevention and screening intervention trials.