scholarly journals Clinician prediction of survival versus the Palliative Prognostic Score: Which approach is more accurate?

2016 ◽  
Vol 64 ◽  
pp. 89-95 ◽  
Author(s):  
David Hui ◽  
Minjeong Park ◽  
Diane Liu ◽  
Carlos Eduardo Paiva ◽  
Sang-Yeon Suh ◽  
...  
Keyword(s):  
Prognostic Score ◽  
Prediction Of Survival

scholarly journals Comparison of The Accuracy of Clinicians’ Prediction of Survival and Palliative Prognostic Score: An East Asian Cross-Cultural Study

2021 ◽  
Author(s):  
Yusuke Hiratsuka ◽  
Seok-Joon Yoon ◽  
Sang-Yeon Suh ◽  
Sung-Eun Choi ◽  
David Hui ◽  
...  
Keyword(s):  
Advanced Cancer ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Prognostic Score ◽  
East Asian ◽  
Prognostic Scores ◽  
Term Survival ◽  
Cross Cultural Study ◽  
Prediction Of Survival ◽  
Short Term Survival

Abstract Purpose:No study has been conducted to compare the clinicians’ prediction of survival (CPS) with Palliative Prognostic Scores (PaP) across countries. We aimed to compare the performance of the CPS in PaP (PaP-CPS), the PaP without the CPS, and the PaP total scores in patients with advanced cancer in three East Asian countries.Methods:We compared the discriminative accuracy of the three predictive models (the PaP-CPS [the score of the categorical CPS of PaP], the PaP without the CPS [sum of the scores of only the objective variables of PaP], and the PaP total score) in patients in Japan, Korea, and Taiwan. We calculated the area under the receiver operating characteristic curve (AUROC) for 30-day survival to compare the discriminative accuracy of these three models.Results:We analyzed 2,072 patients from three countries. The AUROC for the PaP total scores was 0.84 in patients in Japan, 0.76 in Korea, and 0.79 in Taiwan. The AUROC of the PaP-CPS was 0.82 in patients in Japan, 0.75 in Korea, and 0.78 in Taiwan. The AUROC of the PaP without the CPS was 0.75 in patients in Japan, 0.66 in Korea, and 0.67 in Taiwan.Conclusion:The PaP total scores and the PaP-CPS consistently showed similar discriminative accuracy in predicting 30-day survival in patients in Japan, Korea, and Taiwan. It may be sufficient for experienced clinicians to use the CPS alone for estimating the short-term survival (less than one month) of patients with far-advanced cancer. The PaP may help to improve prognostic confidence and further reduce subjective variations.

scholarly journals Predicting survival in patients with advanced cancer in the last weeks of life: How accurate are prognostic models compared to clinicians’ estimates?

2019 ◽  
Vol 34 (1) ◽  
pp. 126-133 ◽  
Author(s):  
David Hui ◽  
Jeremy Ross ◽  
Minjeong Park ◽  
Rony Dev ◽  
Marieberta Vidal ◽  
...  
Keyword(s):  
Palliative Care ◽  
Advanced Cancer ◽  
Prognostic Score ◽  
Prognostic Index ◽  
Prognostic Scores ◽  
Concordance Index ◽  
Prognostic Accuracy ◽  
Prediction Of Survival ◽  
Palliative Prognostic Index ◽  
Performance Scale

Background: It is unclear if validated prognostic scores such as the Palliative Performance Scale, Palliative Prognostic Index, and Palliative Prognostic Score are more accurate than clinician prediction of survival in patients admitted to an acute palliative care unit with only days of survival. Aim: We compared the prognostic accuracy of Palliative Performance Scale, Palliative Prognostic Index, Palliative Prognostic Score, and clinician prediction of survival in this setting. Design: This is a pre-planned secondary analysis of a prospective study. Setting/participants: We assessed Palliative Performance Scale, Palliative Prognostic Index, Palliative Prognostic Score, and clinician prediction of survival at baseline. We computed their prognostic accuracy using the Concordance index and area under the receiver operating characteristics curve for 7-, 14-, and 30-day survival. Results: A total of 204 patients were included with a median overall survival of 10 days (95% confidence interval: 8–11 days). The Concordance index for Palliative Performance Scale, Palliative Prognostic Index, Palliative Prognostic Score, and clinician prediction of survival were 0.74, 0.71, 0.70, and 0.75, respectively. The areas under the curve for these approaches were 0.82–0.87 for 30-day survival, 0.75–0.80 for 14-day survival, and 0.74–0.81 for 7-day survival. The four prognostic approaches had similar accuracies, with the exception of 7-day survival in which clinician prediction of survival was significantly more accurate than Palliative Prognostic Score (difference: 7%) and Palliative Prognostic Index (difference: 8%). Conclusion: In patients with advanced cancer with days of survival, clinician prediction of survival and Palliative Performance Scale alone were as accurate as Palliative Prognostic Score and Palliative Prognostic Index. These four approaches may be useful for prognostication in acute palliative care units. Our findings highlight how patient population may impact the accuracy of prognostic scores.

scholarly journals Multidisciplinary Prognostication Using the Palliative Prognostic Score in an Australian Cancer Center

2015 ◽  
Vol 9 ◽  
pp. PCRT.S24411 ◽  
Author(s):  
Ruwani Mendis ◽  
Wee-Kheng Soo ◽  
Diana Zannino ◽  
Natasha Michael ◽  
Odette Spruyt
Keyword(s):  
Palliative Care ◽  
Overall Survival ◽  
Median Survival ◽  
Survival Probability ◽  
Multidisciplinary Team ◽  
Prognostic Score ◽  
Cancer Center ◽  
Team Approach ◽  
Prediction Of Survival ◽  
Group A

Context Accurate prognostication is important in oncology and palliative care. A multidisciplinary approach to prognostication provides a novel approach, but its accuracy and application is poorly researched. In this study, we describe and analyze our experience of multidisciplinary prognostication in palliative care patients with cancer. Objectives To assess our accuracy of prognostication using multidisciplinary team prediction of survival (MTPS) alone and within the Palliative Prognostic (PaP) Score. Methods This retrospective study included all new patients referred to a palliative care consultation service in a tertiary cancer center between January 2010 and December 2011. Initial assessment data for 421 inpatients and 223 outpatients were analyzed according to inpatient and outpatient groups to evaluate the accuracy of prognostication using MTPS alone and within the PaP score (MTPS-PaP) and their correlation with overall survival. Results Inpatients with MTPS-PaP group A, B, and C had a median survival of 10.9, 3.4, and 0.7 weeks, respectively, and a 30-day survival probability of 81%, 40%, and 10%, respectively. Outpatients with MTPS-PaP group A and B had a median survival of 17.3 and 5.1 weeks, respectively, and a 30-day survival probability of 94% and 50%, respectively. MTPS overestimated survival by a factor of 1.5 for inpatients and 1.2 for outpatients. The MTPS-PaP score correlated better than MTPS alone with overall survival. Conclusion This study suggests that a multidisciplinary team approach to prognostication within routine clinical practice is possible and may substitute for single clinician prediction of survival within the PaP score without detracting from its accuracy. Multidisciplinary team prognostication can assist treating teams to recognize and articulate prognosis, facilitate treatment decisions, and plan end-of-life care appropriately. PaP was less useful in the outpatient setting, given the longer survival interval of the outpatient palliative care patient group.

scholarly journals FDG PET biomarkers for prediction of survival in metastatic melanoma prior to anti-PD1 immunotherapy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
A. Flaus ◽  
V. Habouzit ◽  
N. De Leiris ◽  
J. P. Vuillez ◽  
M. T. Leccia ◽  
...  
Keyword(s):  
Metastatic Melanoma ◽  
Fdg Pet ◽  
Cox Regression ◽  
Prognostic Score ◽  
Survival Rates ◽  
Risk Groups ◽  
Hazard Ratios ◽  
Prediction Of Survival ◽  
Innovative Therapies

AbstractOur aim was to analyse whether biomarkers extracted from baseline 18F-FDG PET before anti-PD1 treatment contribute to prognostic survival information for early risk stratification in metastatic melanoma. Fifty-six patients, without prior systemic treatment, BRAF wild type, explored using 18F-FDG PET were included retrospectively. Our primary endpoint was overall survival (OS). Total metabolic tumoral volume (MTV) and forty-one IBSI compliant parameters were extracted from PET. Parameters associated with outcome were evaluated by a cox regression model and when significant helped build a prognostic score. Median follow-up was 22.1 months and 21 patients died. Total MTV and long zone emphasis (LZE) correlated with shorter OS and served to define three risk categories for the prognostic score. For low, intermediate and high risk groups, survival rates were respectively 91.1% (IC 95 80–1), 56.1% (IC 95 37.1–85) and 19% (IC 95 0.06–60.2) and hazard ratios were respectively 0.11 (IC 95 0.025–0.46), P = 0.0028, 1.2 (IC 95 0.48–2.8), P = 0.74 and 5.9 (IC 95 2.5–14), P < 0.0001. To conclude, a prognostic score based on total MTV and LZE separated metastatic melanoma patients in 3 categories with dramatically different outcomes. Innovative therapies should be tested in the group with the lowest prognosis score for future clinical trials.

scholarly journals Simple and Objective Prediction of Survival in Patients with Lung Cancer: Staging the Host Systemic Inflammatory Response

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Derek Grose ◽  
Graham Devereux ◽  
Louise Brown ◽  
Richard Jones ◽  
Dave Sharma ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Weight Loss ◽  
Inflammatory Response ◽  
Risk Stratification ◽  
Group Performance ◽  
Prognostic Score ◽  
Performance Status ◽  
Glasgow Prognostic Score ◽  
Systemic Inflammatory Response ◽  
Prediction Of Survival

Background. Prediction of survival in patients diagnosed with lung cancer remains problematical. The aim of the present study was to examine the clinical utility of an established objective marker of the systemic inflammatory response, the Glasgow Prognostic Score, as the basis of risk stratification in patients with lung cancer. Methods. Between 2005 and 2008 all newly diagnosed lung cancer patients coming through the multidisciplinary meetings (MDTs) of four Scottish centres were included in the study. The details of 882 patients with a confirmed new diagnosis of any subtype or stage of lung cancer were collected prospectively. Results. The median survival was 5.6 months (IQR 4.8–6.5). Survival analysis was undertaken in three separate groups based on mGPS score. In the mGPS 0 group the most highly predictive factors were performance status, weight loss, stage of NSCLC, and palliative treatment offered. In the mGPS 1 group performance status, stage of NSCLC, and radical treatment offered were significant. In the mGPS 2 group only performance status and weight loss were statistically significant. Discussion. This present study confirms previous work supporting the use of mGPS in predicting cancer survival; however, it goes further by showing how it might be used to provide more objective risk stratification in patients diagnosed with lung cancer.

Prediction of survival after left-sided pancreatic resection for adenocarcinoma: Introduction of a new prognostic score

2019 ◽  
Vol 18 (6) ◽  
pp. 569-575
Author(s):  
Jill Gwiasda ◽  
Zhi Qu ◽  
Harald Schrem ◽  
Felix Oldhafer ◽  
Markus Winny ◽  
...  
Keyword(s):  
Pancreatic Resection ◽  
Prognostic Score ◽  
Prediction Of Survival

Comparison of Objective Prognostic Score and Palliative Prognostic Score performance in inpatients with advanced cancer in Japan and Korea

2021 ◽  
pp. 1-9
Author(s):  
Yusuke Hiratsuka ◽  
Daye Kim ◽  
Sang-Yeon Suh ◽  
Sun-Hyun Kim ◽  
Seok-Joon Yoon ◽  
...  
Keyword(s):  
Advanced Cancer ◽  
Prognostic Score ◽  
Secondary Analysis ◽  
Japanese Patients ◽  
Asian Countries ◽  
Operating Characteristics ◽  
Multicenter Cohort Study ◽  
Multicenter Cohort ◽  
Prediction Of Survival ◽  
Palliative Care Units

Abstract Objective Accurate prognostication is important for patients and their families to prepare for the end of life. Objective Prognostic Score (OPS) is an easy-to-use tool that does not require the clinicians’ prediction of survival (CPS), whereas Palliative Prognostic Score (PaP) needs CPS. Thus, inexperienced clinicians may hesitate to use PaP. We aimed to evaluate the accuracy of OPS compared with PaP in inpatients in palliative care units (PCUs) in three East Asian countries. Method This study was a secondary analysis of a cross-cultural, multicenter cohort study. We enrolled inpatients with far-advanced cancer in PCUs in Japan, Korea, and Taiwan from 2017 to 2018. We calculated the area under the receiver operating characteristics (AUROC) curve to compare the accuracy of OPS and PaP. Results A total of 1,628 inpatients in 33 PCUs in Japan and Korea were analyzed. OPS and PaP were calculated in 71.7% of the Japanese patients and 80.0% of the Korean patients. In Taiwan, PaP was calculated for 81.6% of the patients. The AUROC for 3-week survival was 0.74 for OPS in Japan, 0.68 for OPS in Korea, 0.80 for PaP in Japan, and 0.73 for PaP in Korea. The AUROC for 30-day survival was 0.70 for OPS in Japan, 0.71 for OPS in Korea, 0.79 for PaP in Japan, and 0.74 for PaP in Korea. Significance of results Both OPS and PaP showed good performance in Japan and Korea. Compared with PaP, OPS could be more useful for inexperienced physicians who hesitate to estimate CPS.

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