Palliative Performance Scale Score at 1 Week After Palliative Care Unit Admission is More Useful for Survival Prediction in Patients With Advanced Cancer in South Korea

Background: The Palliative Performance Scale (PPS) is a useful prognostic index in palliative care. Changes in PPS score over time may add useful prognostic information beyond a single measurement. Objective: To investigate the usefulness of repeated PPS measurement to predict survival time of inpatients with advanced cancer admitted to a palliative care unit (PCU) in South Korea. Design: Prospective observational cohort study. Setting/Patients: 138 patients with advanced cancer admitted to a PCU in a university hospital in South Korea from June 2015 to May 2016. Measurements: The PPS score was measured on enrollment and after 1 week. We used Cox regression analyses to calculate hazard ratios (HRs) to demonstrate the relationship between survival time and the groups categorized by PPS and changes in PPS score, after adjusting for clinical variables. Results: There were significant differences in survival time among 3 groups stratified by PPS (10-20, 30-50, and ≥60) after 1 week. A group with a PPS of 10 to 20 at 1 week had the highest risk (HR: 5.18 [95% confidence interval, 1.57-17.04]) for shortened survival. On the contrary, there were no significant differences among these groups by initial PPS alone. Similarly, change in PPS was prognostic; median survival was 13 (10.96-15.04) days for those whose PPS decreased after 1 week and 27 (10.18-43.82) days for those with stable or increased PPS ( P < .001). Conclusions: Measuring PPS over time can be very helpful for predicting survival in terminally ill patients with cancer, beyond a single PPS measure at PCU admission.

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Timing of access to outpatient palliative care services: What’s in a name?

Journal of Clinical Oncology ◽

10.1200/jco.2014.32.31_suppl.10 ◽

2014 ◽

Vol 32 (31_suppl) ◽

pp. 10-10

Author(s):

Shalini Dalal ◽

Sebastian Bruera ◽

Charles Masino ◽

Janet L. Williams ◽

Yi Zhang ◽

...

Keyword(s):

Palliative Care ◽

Survival Time ◽

Advanced Cancer ◽

Median Survival ◽

Cancer Diagnosis ◽

Cox Regression ◽

Transition Period ◽

Patient Access ◽

Name Change ◽

Patient Referrals

10 Background: We have previously shown the name “palliative” to be a barrier to early palliative care (PC) referral. Further, following service name change to supportive care (SC) in late 2007, we immediately observed an increased survival time of about 1.5 months from PC consultation suggesting earlier referral following the name change. This study was conducted to determine the timing of patient access to outpatient PC services over several years period after the name change. Methods: Records of consecutive outpatient referrals in fiscal years (FY) 2007 (pre-name change), 2008 (transition period), 2009-2013 (post-name change) were reviewed. Timing of PC access was determined by 3 time intervals: (a) survival from PC consultation; (b) advanced cancer diagnosis to PC (c) hospital registration to PC; Kruskal-Wallis, Kaplan Meir and Cox regression models were used. Results: 6,624 patients had their first outpatient PC consultation during FY 2007 to 2013. Each year we observed a consistent increase in new patient referrals, as well as a longer median survival time from PC consultation (logrank <0.0001). The table below shows median survival and hazard ratio (HR) for FYs 2008-2013 as compared to FY 2007. In FY 2013 there were 63% greater number of outpatient referrals as compared to FY 2007 (p <0.0001), longer median survival (months) (7.9 vs 4.8; p <0.001), and shorter median interval (months) from advanced cancer diagnosis (5.9 vs 7.8; p< 0.002) and from hospital registration (6.6 vs 14.8; p< 0.0001) to PC consultation. Conclusions: Following the name change of service from PC to SC, there has been consistent annual increase in new patient referrals as well as earlier access to outpatient PC services. The outpatient setting facilitates earlier patient access to SC/PC services and should be established in more centers. [Table: see text]

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

Palliative Medicine ◽

10.1177/0269216319873261 ◽

2019 ◽

Vol 34 (1) ◽

pp. 126-133 ◽

Cited By ~ 2

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.

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Palliative Prognostic Index application at an inpatient palliative care service from a Brazilian tertiary Hospital: A prospective observational study.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.15_suppl.11537 ◽

2019 ◽

Vol 37 (15_suppl) ◽

pp. 11537-11537

Author(s):

Tiago Pugliese Branco ◽

Alze Pereira dos Santos Tavares ◽

Mariana Sarkis Braz ◽

Mariana Ribeiro Monteiro ◽

Ana Beatriz Kinupe Abrahao ◽

...

Keyword(s):

Palliative Care ◽

Cancer Patients ◽

Advanced Cancer ◽

Care Service ◽

Prognostic Index ◽

Palliative Care Service ◽

Tertiary Hospital ◽

Care Physician ◽

Survival Prediction ◽

Advanced Cancer Patients

11537 Background: Palliative Care Index (PPI) has been proposed to improve the accuracy of survival prediction for advanced cancer patients. The aim of this study is to investigate the feasibility and real-world prognosis survival of oncology inpatients from a Brazilian tertiary hospital using PPI. Methods: Hospitalized advanced cancer patients who have been referred to the Palliative Care Team were enrolled from May 2011 to December 2018. The PPI was collected within 24 hours of the referral by the palliative care physician. Primary endpoint was median overall survival (OS), estimated with the use of the Kaplan–Meier method, in three groups: PPI < 4.0; 4.0 ≤ PPI > 6.0 and PPI ≥ 6.0. Secondary endpoints were OS rate at 3-week for patients with PPI ≥ 6.0, and the most accurate PPI value to predict 6 and 3-week survival, calculated by ROC curve. Results: Total of 1.381 patients were included in this cohort with a median age of 68-year-old, and 51.3% of females. The most frequent primary cancer sites were lung/chest (17,2%), colorectal (14,3%), breast (11,2%), and biliopancreatic (10,9%). Among 454 patients with PPI < 4.0, median OS was 44 days (95% CI: 35,5-52,4); 20 days (95% CI: 15,4-24,5) for 260 patients with 4.0≤ PPI < 6.0 and 8 days (95% CI: 7-8,9) between 655 patients with PPI ≥ 6. Differences in OS among the groups adjusted for primary site, age and gender were significant (p < 0,001). OS rate at 3 weeks for PPI≥ 6.0 was 28.1% (OR 5,39 p < 0.001). PPI value of < 5,5 best predicted 6-week OS (79% sensibility, 55% specificity, AUC 0,714) and the PPI value of ≥ 5,5 predicted 3-week OS (67% sensibility, 73% specificity, AUC 0,753). Conclusions: PPI is feasible and suitable for routine clinical practice to predict survival among Brazilian patients with advanced cancer. In our study, PPI 5.5 seems to be the most accurate value to predict survival within 3 weeks.

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Consciousness Levels One Week after Admission to a Palliative Care Unit Improve Survival Prediction in Advanced Cancer Patients

Journal of Palliative Medicine ◽

10.1089/jpm.2014.0220 ◽

2015 ◽

Vol 18 (2) ◽

pp. 170-175

Author(s):

Jaw-Shiun Tsai ◽

Chao-Hsien Chen ◽

Chih-Hsun Wu ◽

Tai-Yuan Chiu ◽

Tatsuya Morita ◽

...

Keyword(s):

Palliative Care ◽

Cancer Patients ◽

Advanced Cancer ◽

Palliative Care Unit ◽

Survival Prediction ◽

Advanced Cancer Patients

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Correlation of Palliative Performance Scale and Survival in Patients With Cancer Receiving Home-Based Palliative Care

Journal of Palliative Care ◽

10.1177/0825859718755249 ◽

2018 ◽

Vol 33 (2) ◽

pp. 95-99 ◽

Cited By ~ 3

Author(s):

Jiaoli Cai ◽

Denise N. Guerriere ◽

Hongzhong Zhao ◽

Peter C. Coyte

Keyword(s):

Palliative Care ◽

Survival Time ◽

Cox Regression ◽

Care Program ◽

Survival Times ◽

Telephone Interviews ◽

Kaplan Meier ◽

Home Based ◽

A Prospective Study ◽

Performance Scale

The main objective of this study was to examine whether and how the Palliative Performance Scale (PPS), a measure of a patient’s function, was predictive of survival time for those in receipt of home-based palliative care. This was a prospective study, which included 194 cancer patients from November 17, 2013, to August 18, 2015. Data were collected from biweekly telephone interviews with caregivers. Kaplan-Meier survival curves were estimated to assess how survival time was correlated with initial PPS scores after admission to the home-based palliative care program. A multivariate extended Cox regression model was used to examine the association between PPS and survival. The results showed that patients with higher PPS scores, that is, better function, had a lower hazard ratio (0.977; 95% confidence interval: 0.965-0.989) and hence longer survival times. The PPS can be used in predicting survival time for home-based palliative care patients.

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Validation of the Palliative Performance Scale for Inpatients Admitted to a Palliative Care Unit in Sydney, Australia

Journal of Pain and Symptom Management ◽

10.1016/s0885-3924(02)00407-4 ◽

2002 ◽

Vol 23 (6) ◽

pp. 455-457 ◽

Cited By ~ 81

Author(s):

Kiran Virik ◽

Glare

Keyword(s):

Palliative Care ◽

Palliative Care Unit ◽

Performance Scale ◽

Sydney Australia

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Antineoplastic therapy use in patients with advanced cancer admitted to an acute palliative care unit at a comprehensive cancer center

Cancer ◽

10.1002/cncr.24942 ◽

2010 ◽

Vol 116 (8) ◽

pp. 2036-2043 ◽

Cited By ~ 34

Author(s):

David Hui ◽

Ahmed Elsayem ◽

Zhijun Li ◽

Maxine De La Cruz ◽

J. Lynn Palmer ◽

...

Keyword(s):

Palliative Care ◽

Antineoplastic Therapy ◽

Advanced Cancer ◽

Palliative Care Unit ◽

Comprehensive Cancer Center ◽

Cancer Center

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Palliative Prognostic Index accuracy of survival prediction in an inpatient palliative care service at a Brazilian tertiary hospital

ecancermedicalscience ◽

10.3332/ecancer.2021.1228 ◽

2021 ◽

Vol 15 ◽

Author(s):

Mauricio Fernandes ◽

Tago Pugliese Branco ◽

Maria Clara Navarro Fernandez ◽

Carolina Paparelli ◽

Mariana Sarkis Braz ◽

...

Keyword(s):

Palliative Care ◽

Care Service ◽

Prognostic Index ◽

Palliative Care Service ◽

Tertiary Hospital ◽

Survival Prediction ◽

Palliative Prognostic Index

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The PROVIEW+ tool: Developing and validating a tool to predict risk of poor performance status and severe symptoms in cancer patients over time.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.12095 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. 12095-12095

Author(s):

Hsien Seow ◽

Rinku Sutradhar ◽

Lisa Catherine Barbera ◽

Peter Tanuseputro ◽

Dawn Guthrie ◽

...

Keyword(s):

Decision Making ◽

Palliative Care ◽

Cancer Patients ◽

Severe Pain ◽

Performance Status ◽

Well Being ◽

Assessment System ◽

Low Performance ◽

Performance Scale ◽

Over Time

12095 Background: There are numerous predictive cancer tools that focus on survival. However, no tools predict risk of low performance status or severe symptoms, which are important for patient decision-making and early integration of palliative care. The aim of this study was to develop and validate a model for all cancer types that predicts the risk for having low performance status and severe symptoms. Methods: A retrospective, population-based, predictive study using linked administrative data from cancer patients from 2008-2015 in Ontario, Canada. Patients were randomly selected for model derivation (60%) and validation (40%). The derivation cohort was used to develop a multivariable logistic regression model to predict the risk of having the reported outcomes in the subsequent 6 months. Model performance was assessed using discrimination and calibration plots. The main outcome was low performance status using the Palliative Performance Scale. Secondary outcomes included severe pain, dyspnea, well-being, and depression using the Edmonton Symptom Assessment System. Outcomes were recalculated after each of 4 annual survivor marks. Results: We identified 255,494 cancer patients (57% female; median age of 64; common cancers were breast (24%) and lung (13%)). At diagnosis, the risk of having low performance status, severe pain, well-being, dyspnea, and depression in 6-months is 1%, 3%, 6%, 13% and 4%, respectively for the reference case (i.e. male, lung cancer, stage I, no symptoms). Generally these covariates increased the outcome risk by > 10% across all models: obstructive lung disease, dementia, diabetes; radiation treatment; hospital admission; high pain; depression; Palliative Performance Scale score of 60-10; issues with appetite; or homecare. Model discrimination was high across all models. Conclusions: The model accurately predicted changing cancer risk for low performance status and severe symptoms over time. Providing accurate predictions of future performance status and symptom severity can support decision-making and earlier initiation of palliative care, even alongside disease modifying therapies.

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