Key result
An 8-factor clinical prediction model for 30-day mortality after colorectal cancer surgery demonstrated good discriminative ability (C statistic 0.82; 95% CI 0.80-0.83).
Why the study?
Because outcomes of modern colorectal cancer surgery have improved, renewed risk stratification is needed to identify patients at high risk for mortality.
Can a clinical prediction model accurately predict 30-day postoperative mortality in patients with colorectal cancer?
Observational (n=84,410)
Yes
Can a clinical prediction model accurately predict 30-day postoperative mortality in patients with colorectal cancer?
Effect estimate: C statistic 0.82 (95% CI 0.80-0.83)
A newly developed clinical prediction model using 8 clinical factors accurately predicts 30-day postoperative mortality in colorectal cancer patients, aiding in clinical decision-making.
May aid preoperative risk stratification in CRC surgery; leaves open external validation before clinical adoption.
BACKGROUND: As the outcome of modern colorectal cancer (CRC) surgery has significantly improved over the years, however, renewed and adequate risk stratification for mortality is important to identify high-risk patients. This population-based study was conducted to analyse postoperative outcomes in patients with CRC and to create a risk model for 30-day mortality. METHODS: Data from the Dutch Colorectal Audit were used to assess differences in postoperative outcomes (30-day mortality, hospital stay, blood transfusion, postoperative complications) in patients with CRC treated from 2009 to 2017. Time trends were analysed. Clinical variables were retrieved (including stage, age, sex, BMI, ASA grade, tumour location, timing, surgical approach) and a prediction model with multivariable regression was computed for 30-day mortality using data from 2009 to 2014. The predictive performance of the model was tested among a validation cohort of patients treated between 2015 and 2017. RESULTS: The prediction model was obtained using data from 51 484 patients and the validation cohort consisted of 32 926 patients. Trends of decreased length of postoperative hospital stay and blood transfusions were found over the years. In stage I-III, postoperative complications declined from 34.3 per cent to 29.0 per cent (P < 0.001) over time, whereas in stage IV complications increased from 35.6 per cent to 39.5 per cent (P = 0.010). Mortality decreased in stage I-III from 3.0 per cent to 1.4 per cent (P < 0.001) and in stage IV from 7.6 per cent to 2.9 per cent (P < 0.001). Eight factors, including stage, age, sex, BMI, ASA grade, tumour location, timing, and surgical approach were included in a 30-day mortality prediction model. The results on the validation cohort documented a concordance C statistic of 0.82 (95 per cent c.i. 0.80 to 0.83) for the prediction model, indicating good discriminative ability. CONCLUSION: Postoperative outcome improved in all stages of CRC surgery in the Netherlands. The developed model accurately predicts postoperative mortality risk and is clinically valuable for decision-making.
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Nes et al. (2022) conducted an observational in Colorectal cancer (n=84,410). 8-factor clinical prediction model was evaluated on 30-day mortality prediction model performance (concordance C statistic) (C statistic 0.82, 95% CI 0.80-0.83). An 8-factor clinical prediction model for 30-day mortality after colorectal cancer surgery demonstrated good discriminative ability (C statistic 0.82; 95% CI 0.80-0.83).
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