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Risk prediction models for colorectal cancer: Evaluating the discrimination due to added biomarkers
Author(s) -
Fang Zhe,
Hang Dong,
Wang Kai,
Joshi Amit,
Wu Kana,
Chan Andrew T.,
Ogino Shuji,
Giovannucci Edward L.,
Song Mingyang
Publication year - 2021
Publication title -
international journal of cancer
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.475
H-Index - 234
eISSN - 1097-0215
pISSN - 0020-7136
DOI - 10.1002/ijc.33621
Subject(s) - medicine , colorectal cancer , logistic regression , stepwise regression , oncology , biomarker , statistic , adiponectin , cancer , obesity , insulin resistance , statistics , biology , mathematics , biochemistry
Most risk prediction models for colorectal cancer (CRC) are based on questionnaires and show a modest discriminatory ability. Therefore, we aim to develop risk prediction models incorporating plasma biomarkers for CRC to improve discrimination. We assessed the predictivity of 11 biomarkers in 736 men in the Health Professionals Follow‐up Study and 639 women in the Nurses' Health Study. We used stepwise logistic regression to examine whether a set of biomarkers improved the predictivity on the basis of predictors in the National Cancer Institute's (NCI) Colorectal Cancer Risk Assessment Tool. Model discrimination was assessed using C‐statistics. Bootstrap with 500 randomly sampled replicates was used for internal validation. The models containing each biomarker generated a C‐statistic ranging from 0.50 to 0.59 in men and 0.50 to 0.54 in women. The NCI model demonstrated a C‐statistic (95% CI) of 0.67 (0.62‐0.71) in men and 0.58 (0.54‐0.63) in women. Through stepwise selection of biomarkers, the C‐statistic increased to 0.70 (0.66‐0.74) in men after adding growth/differentiation factor 15, total adiponectin, sex hormone binding globulin and tumor necrosis factor receptor superfamily member 1B (P for difference = 0.008); and increased to 0.62 (0.57‐0.66) in women after further including insulin‐like growth factor 1 and insulin‐like growth factor‐binding protein 3 ( P for difference = .06). The NCI + selected biomarkers model was internally validated with a C‐statistic (95% CI) of 0.73 (0.70‐0.77) in men and 0.66 (0.61‐0.70) in women. Circulating plasma biomarkers may improve the performance of risk factor‐based prediction model for CRC.