OBJECTIVE: To develop a predicting tool for survival of terminally ill cancer patients. METHODS: This prospective, multicenter study was composed of two cohorts of samples: development and test. In the development sample of terminally ill cancer patients, 32 candidate predictors were studied to develop a new tool, Japan Palliative Oncology Study-Prognostic Index using the Cox proportional hazard model. Then the test sample was studied to validate Japan Palliative Oncology Study-Prognostic Index and compared it with the conventional predicting tools, such as palliative prognostic score and simplified palliative prognostic index. RESULTS: Five significant predictors, physician's clinical prediction of survival, consciousness, pleural effusion, white blood cell count and lymphocyte % were derived from the analysis of 201 patients, and Japan Palliative Oncology Study-Prognostic Index was developed using these predictors. It could divide patients into three risk groups: low (A), intermediate (B) and high (C). Median survival times for Groups A, B and C were 51, 35 and 16 days, respectively. Survival probability for more than 30 days for Groups A, B and C in the development sample was 78%, 61% and 16%, respectively. Japan Palliative Oncology Study-Prognostic Index was studied in subsequent 208 patients for the test sample, and constant results (median survival times for Groups A, B and C; 67, 31 and 10 days, and survival probability for more than 30 days for Groups A, B and C; 81, 48 and 11%) were obtained. Palliative prognostic score can also predict three risk groups well, but simplified palliative prognostic index could not discriminate low risk from intermediate risk group. CONCLUSION: Japan Palliative Oncology Study-Prognostic Index, a tool to predict survival, has been developed. Its reliability should be confirmed further in the future study, comparing with palliative prognostic score.
OBJECTIVE: To develop a predicting tool for survival of terminally ill cancerpatients. METHODS: This prospective, multicenter study was composed of two cohorts of samples: development and test. In the development sample of terminally ill cancerpatients, 32 candidate predictors were studied to develop a new tool, Japan Palliative Oncology Study-Prognostic Index using the Cox proportional hazard model. Then the test sample was studied to validate Japan Palliative Oncology Study-Prognostic Index and compared it with the conventional predicting tools, such as palliative prognostic score and simplified palliative prognostic index. RESULTS: Five significant predictors, physician's clinical prediction of survival, consciousness, pleural effusion, white blood cell count and lymphocyte % were derived from the analysis of 201 patients, and Japan Palliative Oncology Study-Prognostic Index was developed using these predictors. It could divide patients into three risk groups: low (A), intermediate (B) and high (C). Median survival times for Groups A, B and C were 51, 35 and 16 days, respectively. Survival probability for more than 30 days for Groups A, B and C in the development sample was 78%, 61% and 16%, respectively. Japan Palliative Oncology Study-Prognostic Index was studied in subsequent 208 patients for the test sample, and constant results (median survival times for Groups A, B and C; 67, 31 and 10 days, and survival probability for more than 30 days for Groups A, B and C; 81, 48 and 11%) were obtained. Palliative prognostic score can also predict three risk groups well, but simplified palliative prognostic index could not discriminate low risk from intermediate risk group. CONCLUSION: Japan Palliative Oncology Study-Prognostic Index, a tool to predict survival, has been developed. Its reliability should be confirmed further in the future study, comparing with palliative prognostic score.
Authors: Victoria Louise Reid; Rachael McDonald; Amara Callistus Nwosu; Stephen R Mason; Chris Probert; John E Ellershaw; Séamus Coyle Journal: PLoS One Date: 2017-04-06 Impact factor: 3.240
Authors: Eleazar Gil-Herrera; Garrick Aden-Buie; Ali Yalcin; Athanasios Tsalatsanis; Laura E Barnes; Benjamin Djulbegovic Journal: BMC Med Inform Decis Mak Date: 2015-11-25 Impact factor: 2.796