Clinical decision support for precolonoscopy cancer triage: A rule-out-oriented machine learning model for colorectal cancer risk

Table 1 Demographics and colonoscopy findings, n (%)

Variable	Overall (n = 1604)	Malignancy+ (n = 23)	Malignancy- (n = 1581)
Demographics
Age, years, median (IQR)	61 (51-70)	67 (60-74)	61 (51-70)
Male	774 (48.3)	13 (56.5)	761 (48.1)
Female	830 (51.7)	10 (43.5)	820 (51.9)
Colonoscopy findings1
Polyp present	523 (32.6)	-	-
Malignancy present	23 (1.4)	-	-
Diverticulosis	52 (3.2)	-	-
Benign ulcer	33 (2.1)	-	-
Normal colonoscopy	995 (62.0)	-	-
Among polyp-positive patients (n = 523)
Adenoma present	365 (69.8)	-	-

¹Colonoscopy findings are not mutually exclusive; 30 patients had ≥ 2 concurrent findings. Eight patients had non-standard findings (operated colon, ulcerative colitis in remission, or unrecorded) and were retained with malignancy = 0. Adenoma percentage is calculated among the 523 polyp-positive patients, not the full cohort. IQR: Interquartile range.

Table 2 Discrimination and classification performance at the Youden-optimised threshold (repeated stratified 5-fold × 50-repeat cross-validation; 95% confidence intervals from 2000 bootstrap resamples)

Model	Youden cut-off	ROC-AUC (95%CI)	PR-AUC (95%CI)	Brier score (95%CI)	Sensitivity (95%CI)	Specificity (95%CI)	PPV (95%CI)	NPV (95%CI)
All features	0.0046	0.734 (0.637-0.835)	0.078 (0.022-0.191)	0.0152 (0.0099-0.0208)	0.565 (0.455-1.000)	0.846 (0.388-0.905)	0.051 (0.017-0.086)	0.993 (0.989-1.000)
SHAP10	0.0005	0.736 (0.642-0.826)	0.076 (0.020-0.183)	0.0153 (0.0098-0.0208)	0.913 (0.538-1.000)	0.503 (0.485-0.872)	0.026 (0.018-0.067)	0.997 (0.991-1.000)
SHAP5	0.0025	0.711 (0.597-0.812)	0.055 (0.023-0.152)	0.0154 (0.0101-0.0211)	0.739 (0.400-0.963)	0.629 (0.357-0.944)	0.028 (0.017-0.087)	0.994 (0.989-0.999)

All metrics are computed on out-of-fold predictions pooled across 250 cross-validation folds (5 × 50). The Youden cut-off (maximum sensitivity + specificity - 1) is reported as a statistical reference only; clinically relevant operating points (pt = 0.02-0.05) are discussed in the decision curve analysis. CI: Confidence interval; ROC-AUC: Area under the receiver operating characteristic curve; PR-AUC: Area under the precision-recall curve; PPV: Positive predictive value; NPV: Negative predictive value; SHAP: SHapley Additive exPlanations.

Table 3 Calibration performance before and after post-hoc Platt scaling (Cox 1958 framework; fitted on out-of-fold predictions)

Model	Uncalibrated (raw XGBoost output)			After Platt recalibration
	Intercept (95%CI)	Slope (95%CI)	Brier score	Intercept	Slope	Brier score
All features	+0.654 (+0.174 to +1.133)	0.329 (0.171-0.487)	0.0152	0.000	1.003	0.0140
SHAP10	+0.363 (-0.102 to +0.827)	0.315 (0.157-0.472)	0.0153	0.000	1.006	0.0140
SHAP5	-0.042 (-0.493 to +0.409)	0.314 (0.147-0.480)	0.0154	-0.001	1.006	0.0140

The calibration intercept (“calibration-in-the-large”) was obtained as the intercept of a binomial generalised linear model fitted on the observed outcome with the out-of-fold logit predictions as offset; an intercept of 0 indicates no systematic bias. The calibration slope was obtained as the coefficient of a binomial GLM regressing the outcome on the out-of-fold logit; a slope of 1 indicates well-calibrated predictions, whereas values below 1 indicate over-dispersed (too-extreme) predicted probabilities. Platt scaling was applied as a single logistic regression on the out-of-fold logits and restored near-ideal calibration (intercept ≈ 0, slope ≈ 1) for all three models without loss of discrimination, reducing the Brier score uniformly to 0.0140. CI: Confidence interval; XGBoost: Extreme gradient boosting; SHAP: SHapley Additive exPlanations.

Table 4 Likelihood ratios and diagnostic odds ratios at the Youden-optimised threshold (95% confidence intervals from 2000 bootstrap resamples)

Model	Threshold	Sensitivity (95%CI)	Specificity (95%CI)	LR+ (95%CI)	LR- (95%CI)	DOR
All features	0.0046	0.565 (0.364-0.783)	0.846 (0.828-0.863)	3.66 (2.34-5.19)	0.514 (0.257-0.752)	7.1
SHAP10	0.0005	0.913 (0.778-1.000)	0.503 (0.476-0.528)	1.84 (1.55-2.07)	0.173 (0.000-0.445)	10.6
SHAP5	0.0025	0.739 (0.538-0.909)	0.629 (0.605-0.652)	1.99 (1.45-2.46)	0.415 (0.149-0.735)	4.8

Likelihood ratios are prevalence-independent and therefore provide evidence that the model’s performance is not simply a mathematical consequence of the low malignancy prevalence (1.43%). The SHAP10 negative likelihood ratio of 0.173 indicates that a negative model result reduces the post-test odds of malignancy by approximately 5.8-fold, consistent with a rule-out-oriented triage role. CI: Confidence interval; LR+: Positive likelihood ratio = sensitivity/(1 - specificity); LR-: Negative likelihood ratio = (1 - sensitivity)/specificity; DOR: Diagnostic odds ratio. SHAP: SHapley Additive exPlanations.

Table 5 Direction of feature effects in the SHapley Additive exPlanations summary

Feature (Figure 3)	Global direction1	Spearman ρ	High-tail direction2	Pos(SHAP) > 0 in top 20%
Glucose (mg/dL)	Increases	0.718	Decreases	0.234
Platelet (103/μL)	Increases	0.640	Decreases	0.137
SII	Increases	0.490	Decreases	0.019
Age (years)	Increases	0.424	Decreases	0.006
AST (U/L)	Increases	0.377	Decreases	0.216
NLR	Increases	0.368	Increases	0.931
HDL (mg/dL)	Decreases	-0.133	Decreases	0.142
ALT (U/L)	Decreases	-0.187	Decreases	0.000
NHR	Decreases	-0.263	Decreases	0.143
Neutrophil (103/μL)	Decreases	-0.525	Decreases	0.031

¹Global direction was defined by the sign of Spearman correlation between the feature value and its SHapley Additive exPlanations value (positive = higher values tend to increase the predicted malignancy probability; negative = higher values tend to decrease it).

²High-tail direction summarizes SHapley Additive exPlanations sign behavior among observations in the top 20% of the feature distribution, highlighting potential non-linear or threshold effects.

SHAP: SHapley Additive exPlanations; SII: Systemic immune-inflammation index; ALT: Alanine aminotransferase; NLR: Neutrophil to lymphocyte ratio; HDL: High-density lipoprotein; AST: Aspartate aminotransferase; NHR: Neutrophil-to-high-density lipoprotein ratio.