TY - JOUR
T1 - A user-friendly objective prediction model in predicting colorectal cancer based on 234 044 Asian adults in a prospective cohort
AU - Chen, C. H.
AU - Tsai, M. K.
AU - Wen, Christopher
AU - Wen, C. P.
N1 - Publisher Copyright:
© 2021 The Authors
PY - 2021/12
Y1 - 2021/12
N2 - Background: Prediction models of colorectal cancer (CRC) had limited application for not being user-friendly. Whether fecal immunochemical tests (FITs) can help predict CRC has been overlooked. Patients and methods: With 1972 CRCs identified, 234 044 adults aged ≥40 years were successively enrolled between 1994 and 2008. Prediction models were developed by questionnaire/medical screening and quantitative FIT. NNS (number needed to scope to find one cancer) is time dependent, spanning entire study period. Significant ‘risk factors’ were family history, body mass index, smoking, drinking, inactivity, hypertension, diabetes, carcinoembryonic antigen, and C-reactive protein. Results: Positive FIT (≥20 μg/g hemoglobin/feces) had cancer risk 10-fold larger than negative FIT, and within each age group, another 10-fold difference. The C statistic of FIT (0.81) with age and sex alone was superior to the ‘common risk-factors’ model (0.73). NNS, stratified by age and by FIT values, demonstrated a scorecard of cancer risks, like 1/15 or 1/25, in 5 years. When FIT was negative, cancer risk was small (1/750-1/3000 annually). The larger the FIT, the sooner the appearance of CRC. For every 80-μg/g increase of FIT, there were 1.5-year earlier development of CRC incidence and 1-year earlier development of CRC mortality, respectively. Given the same FIT value, CRC events appeared in the proximal colon sooner than the distal colon. Conclusions: A simple user-friendly model based on a single FIT value to predict CRC risk was developed. When positive, NNS offered a simple quantitative value, with a better precision than most risk factors, even combined. When FIT is negative, risk is very small, but requiring a repeat every other year to rule out false negative. FIT values correlated well with CRC prognosis, with worst for proximal CRC.
AB - Background: Prediction models of colorectal cancer (CRC) had limited application for not being user-friendly. Whether fecal immunochemical tests (FITs) can help predict CRC has been overlooked. Patients and methods: With 1972 CRCs identified, 234 044 adults aged ≥40 years were successively enrolled between 1994 and 2008. Prediction models were developed by questionnaire/medical screening and quantitative FIT. NNS (number needed to scope to find one cancer) is time dependent, spanning entire study period. Significant ‘risk factors’ were family history, body mass index, smoking, drinking, inactivity, hypertension, diabetes, carcinoembryonic antigen, and C-reactive protein. Results: Positive FIT (≥20 μg/g hemoglobin/feces) had cancer risk 10-fold larger than negative FIT, and within each age group, another 10-fold difference. The C statistic of FIT (0.81) with age and sex alone was superior to the ‘common risk-factors’ model (0.73). NNS, stratified by age and by FIT values, demonstrated a scorecard of cancer risks, like 1/15 or 1/25, in 5 years. When FIT was negative, cancer risk was small (1/750-1/3000 annually). The larger the FIT, the sooner the appearance of CRC. For every 80-μg/g increase of FIT, there were 1.5-year earlier development of CRC incidence and 1-year earlier development of CRC mortality, respectively. Given the same FIT value, CRC events appeared in the proximal colon sooner than the distal colon. Conclusions: A simple user-friendly model based on a single FIT value to predict CRC risk was developed. When positive, NNS offered a simple quantitative value, with a better precision than most risk factors, even combined. When FIT is negative, risk is very small, but requiring a repeat every other year to rule out false negative. FIT values correlated well with CRC prognosis, with worst for proximal CRC.
KW - colorectal cancer
KW - fecal immunochemical tests
KW - prediction model
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U2 - 10.1016/j.esmoop.2021.100288
DO - 10.1016/j.esmoop.2021.100288
M3 - Article
C2 - 34808523
AN - SCOPUS:85119347474
SN - 2059-7029
VL - 6
JO - ESMO Open
JF - ESMO Open
IS - 6
M1 - 100288
ER -