Clinician prediction of survival versus the Palliative Prognostic Score: Which approach is more accurate?. (September 2016)
- Record Type:
- Journal Article
- Title:
- Clinician prediction of survival versus the Palliative Prognostic Score: Which approach is more accurate?. (September 2016)
- Main Title:
- Clinician prediction of survival versus the Palliative Prognostic Score: Which approach is more accurate?
- Authors:
- Hui, David
Park, Minjeong
Liu, Diane
Paiva, Carlos Eduardo
Suh, Sang-Yeon
Morita, Tatsuya
Bruera, Eduardo - Abstract:
- Abstract: Background: Clinician prediction of survival (CPS) has low accuracy in the advanced cancer setting, raising the need for prediction models such as the palliative prognostic (PaP) score that includes a transformed CPS (PaP-CPS) and five clinical/laboratory variables (PaP-without CPS). However, it is unclear if the PaP score is more accurate than PaP-CPS, and whether PaP-CPS helps to improve the accuracy of PaP score. We compared the accuracy among PaP-CPS, PaP-without CPS and PaP-total score in patients with advanced cancer. Patients and methods: In this prospective study, PaP score was documented in hospitalised patients seen by palliative care. We compared the discrimination of PaP-CPS versus PaP-total and PaP-without CPS versus PaP-total using four indices: concordance statistics, area under the receiver-operating characteristics curve (AUC), net reclassification index and integrated discrimination improvement for 30-day survival and 100-day survival. Results: A total of 216 patients were enrolled with a median survival of 109 d (95% confidence interval [CI] 71–133 d). The AUC for 30-day survival was 0.57 (95% CI 0.47–0.67) for PaP-CPS, 0.78 (95% CI 0.7–0.87) for PaP-without CPS, and 0.73 (95% CI 0.64–0.82) for PaP-total score. PaP-total was significantly more accurate than PaP-CPS according to all four indices for both 30-day and 100-day survival (P < 0.001). PaP-without CPS was significantly more accurate than PaP-total for 30-day survival (P < 0.05).Abstract: Background: Clinician prediction of survival (CPS) has low accuracy in the advanced cancer setting, raising the need for prediction models such as the palliative prognostic (PaP) score that includes a transformed CPS (PaP-CPS) and five clinical/laboratory variables (PaP-without CPS). However, it is unclear if the PaP score is more accurate than PaP-CPS, and whether PaP-CPS helps to improve the accuracy of PaP score. We compared the accuracy among PaP-CPS, PaP-without CPS and PaP-total score in patients with advanced cancer. Patients and methods: In this prospective study, PaP score was documented in hospitalised patients seen by palliative care. We compared the discrimination of PaP-CPS versus PaP-total and PaP-without CPS versus PaP-total using four indices: concordance statistics, area under the receiver-operating characteristics curve (AUC), net reclassification index and integrated discrimination improvement for 30-day survival and 100-day survival. Results: A total of 216 patients were enrolled with a median survival of 109 d (95% confidence interval [CI] 71–133 d). The AUC for 30-day survival was 0.57 (95% CI 0.47–0.67) for PaP-CPS, 0.78 (95% CI 0.7–0.87) for PaP-without CPS, and 0.73 (95% CI 0.64–0.82) for PaP-total score. PaP-total was significantly more accurate than PaP-CPS according to all four indices for both 30-day and 100-day survival (P < 0.001). PaP-without CPS was significantly more accurate than PaP-total for 30-day survival (P < 0.05). Conclusion: We found that PaP score was more accurate than CPS, and the addition of CPS to the prognostic model reduced its accuracy. This study highlights the limitations of clinical gestalt and the need to use objective prognostic factors and models for survival prediction. Highlights: Clinician prediction of survival (CPS) has low accuracy in the advanced cancer setting. We directly compared the Palliative Prognostic Score to CPS, and found that the prognostic score was more accurate. Palliative Prognostic Score without CPS was even more accurate than when CPS was included as part of the score. This study highlights the need to use objective prognostic factors/models for prognostication instead of clinical gestalt. … (more)
- Is Part Of:
- European journal of cancer. Volume 64(2016)
- Journal:
- European journal of cancer
- Issue:
- Volume 64(2016)
- Issue Display:
- Volume 64, Issue 2016 (2016)
- Year:
- 2016
- Volume:
- 64
- Issue:
- 2016
- Issue Sort Value:
- 2016-0064-2016-0000
- Page Start:
- 89
- Page End:
- 95
- Publication Date:
- 2016-09
- Subjects:
- Clinical prediction rule -- Forecasting -- Prognosis -- Neoplasms -- Statistical data analysis -- Survival
Cancer -- Periodicals
Neoplasms -- Periodicals
Cancer -- Périodiques
Cancer
Tumors
Electronic journals
Periodicals
Electronic journals
616.994 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09598049 ↗
http://rzblx1.uni-regensburg.de/ezeit/warpto.phtml?colors=7&jour_id=2879 ↗
http://www.clinicalkey.com/dura/browse/journalIssue/09598049 ↗
http://www.clinicalkey.com.au/dura/browse/journalIssue/09598049 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ejca.2016.05.009 ↗
- Languages:
- English
- ISSNs:
- 0959-8049
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3829.725100
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British Library STI - ELD Digital store - Ingest File:
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