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Validation of Modified Models of Objective Prognostic Score in Patients With Advanced Cancer.

Seok-Joon YoonSang-Yeon SuhYusuke HiratsukaSung-Eun ChoiSun-Hyun KimSu-Jin KohShin Ae ParkJi-Yeon SeoJung Hye KwonJeanno ParkYoungmin ParkSun Wook HwangEon Sook LeeHong-Yup AhnShao-Yi ChengPing-Jen ChenTakashi YamaguchiSatoru TsunetoMasanori MoriTatsuya Morita
Published in: Journal of palliative medicine (2023)
Background: The objective prognostic score (OPS) needs to be modified to reflect practical palliative care circumstances. Objectives: We aimed to validate modified models of OPS with few or no laboratory tests for patients with advanced cancer. Design: An observational study was performed. Setting/Subjects: A secondary analysis of an international, multicenter cohort study of patients in East Asia was performed. The subjects were inpatients with advanced cancer in the palliative care unit. Measurements: We developed two modified OPS (mOPS) models to predict two-week survival: mOPS-A consisted of two symptoms, two objective signs, and three laboratory results, while mOPS-B consisted of three symptoms, two signs, and no laboratory data. We compared the accuracy of the prognostic models using sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). Calibration plots for two-week survival and net reclassification indices (NRIs) were compared for the two models. Survival differences between higher and lower score groups of each model were identified by the log-rank test. Results: We included a total of 1796 subjects having median survival of 19.0 days. We found that mOPS-A had higher specificity (0.805-0.836) and higher AUROCs (0.791-0.797). In contrast, mOPS-B showed higher sensitivity (0.721-0.725) and acceptable AUROCs (0.740-0.751) for prediction of two-week survival. Two mOPSs showed good concordance in calibration plots. Considering NRIs, replacing the original OPS with mOPSs improved overall reclassification (absolute NRI: 0.47-4.15%). Higher score groups of mOPS-A and mOPS-B showed poorer survival than those of lower score groups ( p  < 0.001). Conclusions: mOPSs used reduced laboratory data and had relatively good accuracy for predicting survival in advanced cancer patients receiving palliative care.
Keyphrases
  • advanced cancer
  • palliative care
  • free survival
  • magnetic resonance imaging
  • clinical trial
  • magnetic resonance
  • depressive symptoms
  • randomized controlled trial
  • machine learning
  • cross sectional
  • double blind