ArticleJournal of cardiothoracic surgery2026
Development and validation of a nomogram for predicting heterogeneous patient-reported outcome recovery trajectories after lung cancer surgery: a retrospective study.
Article in Journal of cardiothoracic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundPostoperative recovery in lung cancer patients is heterogeneous, yet traditional assessments often fail to capture this variability. This study aimed to identify distinct patient-reported outcome (PRO) recovery trajectories for core postoperative symptoms, validate them against objective pulmonary function, and develop a preoperative nomogram to predict unfavorable recovery.
methodsA single-center retrospective cohort study was conducted including 528 patients who underwent minimally invasive surgery for non-small cell lung cancer. Longitudinal PROs (cough, dyspnea, pain, fatigue) were collected over four postoperative weeks via a digital platform. Growth mixture modeling (GMM) was used to identify recovery trajectories, which were dichotomized into favorable and unfavorable groups. The trajectories were validated against the postoperative change in forced expiratory volume in 1 s (△FEV1%). A predictive nomogram was developed using LASSO regression and multivariable logistic regression, with internal validation via bootstrapping.
resultsGMM identified three distinct trajectories per symptom, consistently including a persistent high-symptom group. The composite unfavorable trajectory group showed significantly worse △FEV1% than the favorable group (5.2% vs. 12.8%, p < 0.001). The final nomogram incorporated five predictors: age, Charlson Comorbidity Index, preoperative handgrip strength, preoperative depression/anxiety, and extent of resection. The model demonstrated excellent discrimination (C-index = 0.845, bootstrap-corrected 0.832), good calibration, and clinical utility across a wide threshold range.
conclusionThis study confirms the heterogeneity of postoperative recovery and provides a validated, easy-to-use nomogram for preoperative prediction of unfavorable PRO recovery trajectories. The tool may facilitate early risk stratification and personalized interventions to improve recovery outcomes.
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