Literature DB >> 18588404

Can physicians accurately predict survival time in patients with metastatic cancer? Analysis of RTOG 97-14.

William F Hartsell1, Michelle Desilvio, Deborah Watkins Bruner, Charles Scarantino, Robert Ivker, Mack Roach, John Suh, William F Demas, Benjamin Movsas, Ivy A Petersen, Andre A Konski.   

Abstract

PURPOSE: To determine if physician prediction of survival duration (PSD) is accurate for patients with metastatic breast or prostate cancer.
METHODS: Radiation Therapy Oncology Group 9714 (RTOG 9714) was a randomized comparison of radiotherapy schedules for treatment of bone metastases. The treating physician assigned a baseline Karnofsky Performance Score (KPS) and predicted survival duration at study entry. Patients completed the Functional Assessment of Cancer Therapy (FACT). These three were compared to actual survival time.
RESULTS: Eight hundred ninety-eight patients were eligible and analyzable. Actual median survival was 9.3 months. The median PSD was 12 months. PSD, KPS, and FACT were all moderately correlated with actual survival. Patients with higher KPS had a longer survival time (882 patients, Spearman's rho = 0.259, p < 0.0001). The median survival of the 618 expired patients is 6.5 months (PSD was 12 months). The PSD was within 1 month of actual survival in 61 (10%), with 177 (29%) patients surviving more than 1 month longer than predicted and 375 (61%) surviving more than 1 month less than predicted. A univariate analysis of actual overall survival was performed, dividing the PSD into 4 groups. For predicted survivals of 6 months or less, less than 6 to less than 12 months, 12 months, and more than 12 months, median actual survivals were 7.0, 7.2, 9.7. and 13.5 months (p < 0.0001).
CONCLUSIONS: KPS, FACT scores, and PSD all are correlated with actual survival. Physicians on this study were able to predict which patients would have longer survival times, although prediction of survival was optimistic compared to actual survival by an average of 3 months.

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Year:  2008        PMID: 18588404     DOI: 10.1089/jpm.2007.0259

Source DB:  PubMed          Journal:  J Palliat Med        ISSN: 1557-7740            Impact factor:   2.947


  16 in total

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2.  How palliative care professionals deal with predicting life expectancy at the end of life: predictors and accuracy.

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3.  Palliative radiotherapy during the last month of life: Predictability for referring physicians and radiation oncologists.

Authors:  Carsten Nieder; Kent Angelo; Astrid Dalhaug; Adam Pawinski; Ellinor Haukland; Jan Norum
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4.  External Validation and Optimization of the SPRING Model for Prediction of Survival After Surgical Treatment of Bone Metastases of the Extremities.

Authors:  Michala Skovlund Sørensen; Thomas Alexander Gerds; Klaus Hindsø; Michael Mørk Petersen
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7.  Automated model versus treating physician for predicting survival time of patients with metastatic cancer.

Authors:  Michael F Gensheimer; Sonya Aggarwal; Kathryn R K Benson; Justin N Carter; A Solomon Henry; Douglas J Wood; Scott G Soltys; Steven Hancock; Erqi Pollom; Nigam H Shah; Daniel T Chang
Journal:  J Am Med Inform Assoc       Date:  2021-06-12       Impact factor: 4.497

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Authors:  Miriam Vázquez; Manuel Altabas; Diana C Moreno; Abraham A Geng; Santiago Pérez-Hoyos; Jordi Giralt
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Authors:  Jonathan Agner Forsberg; John Eberhardt; Patrick J Boland; Rikard Wedin; John H Healey
Journal:  PLoS One       Date:  2011-05-13       Impact factor: 3.240

10.  The advantage of 3D conformal treatment of lumbar spine metastases in comparison to traditional PA or AP-PA techniques: restoring an intermediate niche of therapeutic sophistication.

Authors:  Viacheslav Soyfer; Benjamin W Corn; Natan Shtraus; Dan Schifter; Haim Tempelhof
Journal:  Radiat Oncol       Date:  2013-02-12       Impact factor: 3.481

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