Objectives: To develop and validate a clinical prediction model (CPM) for survival in hypopharynx cancer, thereby aiming to improve individualized estimations of survival.
Methods: Retrospective cohort study of hypopharynx cancer patients. We randomly split the cohort into a derivation and validation dataset. The model was fitted on the derivation dataset and validated on the validation dataset. We used a Cox's proportional hazard model and least absolute shrinkage and selection operator (LASSO) selection. Performance (discrimination and calibration) of the CPM was tested.
Results: The final model consisted of gender, subsite, TNM classification, Adult Comorbidity Evaluation-27 score (ACE27), body mass index (BMI), hemoglobin, albumin, and leukocyte count. Of these, TNM classification, ACE27, BMI, hemoglobin, and albumin had independent significant associations with survival. The C Statistic was 0.62 after validation. The model could significantly identify clinical risk groups.
Conclusions: ACE27, BMI, hemoglobin, and albumin are independent predictors of overall survival. The identification of high-risk patients can be used in the counseling process and tailoring of treatment strategy or follow-up.
Level of evidence: 4 Laryngoscope, 130:2166-2172, 2020.
Keywords: Hypopharynx cancer; LASSO; chemoradiotherapy; clinical prediction model; survival; total laryngectomy.
© 2019 The Authors. The Laryngoscope published by Wiley Periodicals, Inc. on behalf of The American Laryngological, Rhinological and Otological Society, Inc.