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Prognostication Using the Japanese Risk Calculator for Lung Cancer Surgery
Hiroki Ozawa1, Yosuke Matsuura2, Kohei Hashimoto2
1Department of Thoracic Surgical Oncology, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo, Japan; First Department of Surgery, Hamamatsu University School of Medicine, Shizuoka, Japan.
Introduction:
Various calculation models to predict surgical risk have been developed globally. These have been reported to be helpful for estimating the long-term prognosis. In Japan, a similar model for lung cancer surgery was developed in 2017; however, there have been no reports investigating its association with the long-term prognosis. The objective of this study was to assess the association of the model's predictions with the long-term prognosis.
Patients And Methods:
In this retrospective single-institutional study, we analyzed lung cancer patients who underwent radical lobectomy between 2010 and 2016. We calculated the predicted rates of mortality (PRM) and composite outcomes of mortality with major morbidity (PRMM) in eligible patients (N = 1054) using this model and classified them into 2 classes (class A, PRM ≥0.8% and PRMM ≥5.9%; class B, others) based on their models' predictions. We assessed the prognostic impact and clinical utility of the model's predictions.
Results:
Class A included patients with significantly poorer postoperative overall survival than class B (log-rank, P < .001; hazard ratio, 3.160; 95% confidence interval, 2.390-4.178). Time-dependent receiver operating characteristic curve analyses revealed that the model's predictions correlated strongly with 1- and 2-year overall survival and decision curve analysis showed that they had high net benefits for prediction of those.
Conclusion:
The Japanese risk calculator could stratify the long-term prognosis for lung cancer patients after surgery. This model may be a valuable tool not only for multidisciplinary thoracic oncology teams to discuss treatment strategies for high-risk cases but also for them to share the decision-making process with patients.
