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      Prognostication in palliative radiotherapy—ProPaRT: Accuracy of prognostic scores

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          Abstract

          Background

          Prognostication can be used within a tailored decision-making process to achieve a more personalized approach to the care of patients with cancer. This prospective observational study evaluated the accuracy of the Palliative Prognostic score (PaP score) to predict survival in patients identified by oncologists as candidates for palliative radiotherapy (PRT). We also studied interrater variability for the clinical prediction of survival and PaP scores and assessed the accuracy of the Survival Prediction Score (SPS) and TEACHH score.

          Materials and methods

          Consecutive patients were enrolled at first access to our Radiotherapy and Palliative Care Outpatient Clinic. The discriminating ability of the prognostic models was assessed using Harrell’s C index, and the corresponding 95% confidence intervals (95% CI) were obtained by bootstrapping.

          Results

          In total, 255 patients with metastatic cancer were evaluated, and 123 (48.2%) were selected for PRT, all of whom completed treatment without interruption. Then, 10.6% of the irradiated patients who died underwent treatment within the last 30 days of life. The PaP score showed an accuracy of 74.8 (95% CI, 69.5–80.1) for radiation oncologist (RO) and 80.7 (95% CI, 75.9–85.5) for palliative care physician (PCP) in predicting 30-day survival. The accuracy of TEACHH was 76.1 (95% CI, 70.9–81.3) and 64.7 (95% CI, 58.8–70.6) for RO and PCP, respectively, and the accuracy of SPS was 70 (95% CI, 64.4–75.6) and 72.8 (95% CI, 67.3–78.3).

          Conclusion

          Accurate prognostication can identify candidates for low-fraction PRT during the last days of life who are more likely to complete the planned treatment without interruption.

          All the scores showed good discriminating capacity; the PaP had the higher accuracy, especially when used in a multidisciplinary way.

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          Most cited references43

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          Prognostic factors in advanced cancer patients: evidence-based clinical recommendations--a study by the Steering Committee of the European Association for Palliative Care.

          To offer evidence-based clinical recommendations concerning prognosis in advanced cancer patients. A Working Group of the Research Network of the European Association for Palliative Care identified clinically significant topics, reviewed the studies, and assigned the level of evidence. A formal meta-analysis was not feasible because of the heterogeneity of published studies and the lack of minimal standards in reporting results. A systematic electronic literature search within the main available medical literature databases was performed for each of the following four areas identified: clinical prediction of survival (CPS), biologic factors, clinical signs and symptoms and psychosocial variables, and prognostic scores. Only studies on patients with advanced cancer and survival < or = 90 days were included. A total of 38 studies were evaluated. Level A evidence-based recommendations of prognostic correlation could be formulated for CPS (albeit with a series of limitations of which clinicians must be aware) and prognostic scores. Recommendations on the use of other prognostic factors, such as performance status, symptoms associated with cancer anorexia-cachexia syndrome (weight loss, anorexia, dysphagia, and xerostomia), dyspnea, delirium, and some biologic factors (leukocytosis, lymphocytopenia, and C-reactive protein), reached level B. Prognostication of life expectancy is a significant clinical commitment for clinicians involved in oncology and palliative care. More accurate prognostication is feasible and can be achieved by combining clinical experience and evidence from the literature. Using and communicating prognostic information should be part of a multidisciplinary palliative care approach.
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            Evaluating claims-based indicators of the intensity of end-of-life cancer care.

            To evaluate measures that could use existing administrative data to assess the intensity of end-of-life cancer care. Benchmarking standards and statistical variation were evaluated using Medicare claims of 48,906 patients who died from cancer from 1991 through 1996 in 11 regions of the United States. We assessed accuracy by comparing administrative data to 150 medical records in one hospital and affiliated cancer treatment center. Systems not providing overly aggressive care near the end of life would be ones in which less than 10% of patients receive chemotherapy in the last 14 days of life, less than 2% start a new chemotherapy regimen in the last 30 days of life, less than 4% have multiple hospitalizations or emergency room visits or are admitted to the intensive care unit (ICU) in the last month of life, and less than 17% die in an acute care institution. At least 55% of patients would receive hospice services before death from cancer, and less than 8% of those would be admitted to hospice within only 3 days of death. All measures were found to have accuracy ranging from 85 to 97% and 2- to 5-fold adjusted variability between the 5th and 95th percentiles of performance. The usefulness of these measures will depend on whether the concept of intensity of care near death can be further validated as an acceptable and important quality issue among patients, their families, health care providers, and other stakeholders in oncology.
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              Relationship between cancer patients' predictions of prognosis and their treatment preferences.

              Jane Weeks (1998)
              Previous studies have documented that cancer patients tend to overestimate the probability of long-term survival. If patient preferences about the trade-offs between the risks and benefits associated with alternative treatment strategies are based on inaccurate perceptions of prognosis, then treatment choices may not reflect each patient's true values. To test the hypothesis that among terminally ill cancer patients an accurate understanding of prognosis is associated with a preference for therapy that focuses on comfort over attempts at life extension. Prospective cohort study. Five teaching hospitals in the United States. A total of 917 adults hospitalized with stage III or IV non-small cell lung cancer or colon cancer metastatic to liver in phases 1 and 2 of the Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatments (SUPPORT). Proportion of patients favoring life-extending therapy over therapy focusing on relief of pain and discomfort, patient and physician estimates of the probability of 6-month survival, and actual 6-month survival. Patients who thought they were going to live for at least 6 months were more likely (odds ratio [OR], 2.6; 95% confidence interval [CI], 1.8-3.7) to favor life-extending therapy over comfort care compared with patients who thought there was at least a 10% chance that they would not live 6 months. This OR was highest (8.5; 95% CI, 3.0-24.0) among patients who estimated their 6-month survival probability at greater than 90% but whose physicians estimated it at 10% or less. Patients overestimated their chances of surviving 6 months, while physicians estimated prognosis quite accurately. Patients who preferred life-extending therapy were more likely to undergo aggressive treatment, but controlling for known prognostic factors, their 6-month survival was no better. Patients with metastatic colon and lung cancer overestimate their survival probabilities and these estimates may influence their preferences about medical therapies.
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                Author and article information

                Contributors
                Journal
                Front Oncol
                Front Oncol
                Front. Oncol.
                Frontiers in Oncology
                Frontiers Media S.A.
                2234-943X
                16 August 2022
                2022
                : 12
                : 918414
                Affiliations
                [1] 1 Medical Oncology Unit, Department of Specialized, Experimental and Diagnostic Medicine (DIMES), University of Bologna , Bologna, Italy
                [2] 2 Unit of Biostatistics and Clinical Trials, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori” , Meldola, Italy
                [3] 3 Radiotherapy Unit, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori” , Meldola, Italy
                [4] 4 Palliative Care Unit, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori” , Meldola, Italy
                [5] 5 Palliative Care Unit, Azienda Unità Sanitaria Locale (AUSL) Romagna , Forlì, Italy
                Author notes

                Edited by: Jared Robbins, University of Arizona, United States

                Reviewed by: Robert Olson, Faculty of Medicine, University of British Columbia, Canada; Shalini Vinod, Liverpool Hospital, Australia

                *Correspondence: Emanuela Scarpi, emanuela.scarpi@ 123456irst.emr.it

                This article was submitted to Cancer Epidemiology and Prevention, a section of the journal Frontiers in Oncology

                Article
                10.3389/fonc.2022.918414
                9425085
                3d85974e-89a2-4eaa-a705-225242cb7000
                Copyright © 2022 Maltoni, Scarpi, Dall’Agata, Micheletti, Pallotti, Pieri, Ricci, Romeo, Tenti, Tontini and Rossi

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 12 April 2022
                : 22 July 2022
                Page count
                Figures: 1, Tables: 4, Equations: 0, References: 44, Pages: 10, Words: 5205
                Categories
                Oncology
                Original Research

                Oncology & Radiotherapy
                outpatient palliative care,palliative radiotherapy,prognostication,aggressiveness of care,personalized palliative care

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