A Risk Model to Predict the Delivery of Adjuvant Chemotherapy Following Lung Resection in Patients With Pathologically Positive Lymph Nodes
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abstract
To investigate factors associated with the ability to receive adjuvant chemotherapy in patients with pathological N1 and N2 stage after anatomic lung resections for non-small cell lung cancer (NSCLC). Multicenter retrospective analysis on 707 consecutive patients found pathologic N1 (pN1) or N2 (pN2) disease following anatomic lung resections for NSCLC (2014-2019). Multiple imputation logistic regression was used to identify factors associated with adjuvant chemotherapy and to develop a model to predict the probability of starting this treatment. The model was externally validated in a population of 253 patients. In the derivation set, 442 patients were pN1 and 265 pN2. 58% received at least 1 cycle of adjuvant chemotherapy. The variables significantly associated with the probability of starting chemotherapy after multivariable regression analysis were: younger age (p < 0.0001), Body Mass Index (BMI) (p = 0.031), Forced Expiratory Volume in 1 second (FEV1) (p = 0.037), better performance status (PS) (p < 0.0001), absence of chronic kidney disease (CKD) (p = 0.016), resection lesser than pneumonectomy (p = 0.010). The logit of the prediction model was: 6.58 -0.112 x age +0.039 x BMI +0.009 x FEV1 -0.650 x PS -1.388 x CKD -0.550 x pneumonectomy. The predicted rate of adjuvant chemotherapy in the validation set was 59.2 and similar to the observed 1 (59%, p = 0.87) confirming the model performance in external setting. This study identified several factors associated with the probability of initiating adjuvant chemotherapy after lung resection in node-positive patients. This information can be used during preoperative multidisciplinary meetings and patients counseling to support decision-making process regarding the timing of systemic treatment.
