Predicting serious complications in patients with cancer and pulmonary embolism using decision tree modelling: the...

Our objective was to develop a prognostic stratification tool that enables patients with cancer and pulmonary embolism (PE), whether incidental or symptomatic, to be classified according to the risk of serious complications within 15 days.

The sample comprised cases from a national registry of pulmonary thromboembolism in patients with cancer (1075 patients from 14 Spanish centres). Diagnosis was incidental in 53.5% of the events in this registry. The Exhaustive CHAID analysis was applied with 10-fold cross-validation to predict development of serious complications following PE diagnosis.

About 208 patients (19.3%, 95% confidence interval (CI), 17.1-21.8%) developed a serious complication after PE diagnosis. The 15-day mortality rate was 10.1%, (95% CI, 8.4-12.1%). The decision tree detected six explanatory covariates: Hestia-like clinical decision rule (any risk criterion present vs none), Eastern Cooperative Group performance scale (ECOG-PS; <2 vs ⩾2), O₂ saturation (<90 vs ⩾90%), presence of PE-specific symptoms, tumour response (progression, unknown, or not evaluated vs others), and primary tumour resection. Three risk classes were created (low, intermediate, and high risk). The risk of serious complications within 15 days increases according to the group: 1.6, 9.4, 30.6%; P<0.0001. Fifteen-day mortality rates also rise progressively in low-, intermediate-, and high-risk patients: 0.3, 6.1, and 17.1%; P<0.0001. The cross-validated risk estimate is 0.191 (s.e.=0.012). The optimism-corrected area under the receiver operating characteristic curve is 0.779 (95% CI, 0.717-0.840).

We have developed and internally validated a prognostic index to predict serious complications with the potential to impact decision-making in patients with cancer and PE.