Utility of Palliative Prognostic Index in Predicting Survival Outcomes in Patients With Hematological Malignancies in the Acute Ward Setting

Lee, Shu‐Hui; Chou, Wen‐Chi; Yang, Hsin-Yi; Chen, Chia-Chia; Chang, Hong-Yeh; Wang, Po‐Nan; Kuo, Ming‐Chung; Kao, Yu-Feng; Ho, Lun‐Hui; Hsueh, Shun‐Wen; Kao, Chen-Yi; Hsueh, William; Hung, Chen-Yu; Hung, Yu‐Shin

doi:10.1177/10499091211028820

Cited by 7 publications

(12 citation statements)

References 30 publications

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“…42 Although PC prognostic indices can be used to predict life expectancy, they do not necessarily predict other outcome measures in HM such as likelihood of readmission. 43 Therefore, interprofessional discharge planning that involves PC integration could be beneficial to improve postdischarge quality measures. Although we did not directly examine additional value-based care measures such as cost or patient satisfaction, these could be assessed in future studies focusing on these important areas related to PC integration in caring for patients with HM.…”

Section: Jco Oncology Practice E691mentioning

confidence: 99%

Outcomes of Patients With Hematologic Malignancies Who Received Inpatient Palliative Care Consultation

Pasquarella

Islam

Ramdhanny

et al. 2022

JCO Oncology Practice

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PURPOSE: Palliative care (PC) plays an established role in improving outcomes in patients with solid tumors, yet these services are underutilized in hematologic malignancies (HMs). We reviewed records of hospitalized patients with active HM to determine associations between PC consultation and length of stay, intensive care unit stay, 30-day readmission, and 6-month mortality compared with those who were not seen by PC. METHODS: We reviewed all oncology admissions at our institution between 2013 and 2019 and included patients with HM actively on treatment, stratified by those seen by PC to controls not seen by PC. Groups were compared using Wilcoxon rank-sum, chi-square, and Fisher's exact tests on the basis of the type and distribution of data. Multiple logistic regression models with stepwise variable selection methods were used to find predictors of outcomes. RESULTS: Three thousand six hundred fifty-four admissions were reviewed, among which 370 unique patients with HM were included. Among these, 102 (28%) patients saw PC, whereas the remaining 268 were controls with similar comorbidities. When compared with controls, PC consultation was associated with a statistically significant reduction in 30-day readmissions (16% v 27%; P = .024), increased length of stay (11.5 v 6 days; P < .001), increased intensive care unit admission (28% v 9%; P < .001), and increased 6-month mortality (67% v 15%; P < .001). These data were confirmed in multivariable models. CONCLUSION: In this retrospective study, more than two thirds of patients with HM did not receive PC consultation despite having similar comorbidities, suggesting that inpatient PC consultation is underutilized in patients with HM, despite the potential for decreased readmission rates.

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Section: Jco Oncology Practice E691mentioning

confidence: 99%

Outcomes of Patients With Hematologic Malignancies Who Received Inpatient Palliative Care Consultation

Pasquarella

Islam

Ramdhanny

et al. 2022

JCO Oncology Practice

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“…16 Recent studies have reported the utility of PPI for predicting the life expectancy of patients with hematological malignancies. 17,18 It is interesting and important that this study suggested the utility of PPI for end-of-life prognosis not only in advanced hematological malignancies but also in the chemotherapy group. Moreover, it has been suggested that inflammationbased prognostic scores, such as GPS, PNI, and CONUT, are related to survival in hematological malignancies as predictors of the prognosis of chemotherapy.…”

Section: Discussionmentioning

confidence: 91%

Factors Associated With Survival in Patients With End-of-Life Hematological Malignancies Who Received Chemotherapy: A Retrospective Single-Institution Study

Iizuka-Honma

Mitsumori

Takizawa

et al. 2022

Am J Hosp Palliat Care

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Background Clinicians can appropriately terminate treatment or reduce treatment intensity by determining prognostic factors of end-of-life chemotherapy. In particular, it provides important information for patients with hematological malignancies who receive chemotherapy until near-the-end of life compared with patients with solid tumors. This study aimed to clarify whether existing prognostic tools are associated with the survival in patients with end-of-life hematological malignancies who received chemotherapy. Methods We retrospectively reviewed the records of 247 patients diagnosed with hematological malignancies and died at our university hospital hematology ward between May 2015 and May 2021. We performed multivariate analysis in 82 (33.2%) patients who received end-of-life chemotherapy using the Palliative Prognostic Index (PPI) and inflammation-based prognostic models, such as the Glasgow Prognostic Score (GPS), Prognostic Nutritional Index (PNI), and Controlling Nutrition Status (CONUT). Results On comparing 82 patients who received end-of-life chemotherapy with 165 patients who did not, the proportion of patients with PPI group A, GPS score = 0, and CONUT normal/mild was significantly higher among patients who received chemotherapy. In multivariate analysis, we identified PPI groups B (2.0 < PPI ≤ 4.0) and C (PPI > 4.0) [hazard ratio (HR) 2.1290, 95% CI 1.1830-3.828, P = .01166, respectively] and age ≥ 65 years (HR 2.0170, 95% CI 1.1280-3.607, P = .01805) were associated with overall survival. Conclusion PPI use and age were independent associating factors for patients with hematological malignancies receiving end-of-life chemotherapy. PPI, a popular prognostic tool may be helpful for patients and hematologists to make decisions about end-of-life care.

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“…Most were conducted in palliative care units/team consultations ( n = 20), followed by hospices ( n = 8), mixed settings ( n = 5), acute wards ( n = 4) and home/community palliative care settings ( n = 2) (Table 1). Most PPI assessments were conducted by doctors only, nurses only 24,66,83 or both. 53,60,62,76 The PPI was used to predict numerous survival durations.…”

Section: Resultsmentioning

confidence: 99%

Performance of the Palliative Prognostic Index for cancer patients: A systematic review and meta-analysis

Yoong,

Porock,

Whitty

et al. 2023

Palliat Med

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Background: Clinician predicted survival for cancer patients is often inaccurate, and prognostic tools may be helpful, such as the Palliative Prognostic Index (PPI). The PPI development study reported that when PPI score is greater than 6, it predicted survival of less than 3 weeks with a sensitivity of 83% and specificity of 85%. When PPI score is greater than 4, it predicts survival of less than 6 weeks with a sensitivity of 79% and specificity of 77%. However, subsequent PPI validation studies have evaluated various thresholds and survival durations, and it is unclear which is most appropriate for use in clinical practice. With the development of numerous prognostic tools, it is also unclear which is most accurate and feasible for use in multiple care settings. Aim: We evaluated PPI model performance in predicting survival of adult cancer patients based on different thresholds and survival durations and compared it to other prognostic tools. Design: This systematic review and meta-analysis was registered in PROSPERO (CRD42022302679). We calculated the pooled sensitivity and specificity of each threshold using bivariate random-effects meta-analysis and pooled diagnostic odds ratio of each survival duration using hierarchical summary receiver operating characteristic model. Meta-regression and subgroup analysis were used to compare PPI performance with clinician predicted survival and other prognostic tools. Findings which could not be included in meta-analyses were summarised narratively. Data sources: PubMed, ScienceDirect, Web of Science, CINAHL, ProQuest and Google Scholar were searched for articles published from inception till 7 January 2022. Both retrospective and prospective observational studies evaluating PPI performance in predicting survival of adult cancer patients in any setting were included. The Prediction Model Risk of Bias Assessment Tool was used for quality appraisal. Results: Thirty-nine studies evaluating PPI performance in predicting survival of adult cancer patients were included ( n = 19,714 patients). Across meta-analyses of 12 PPI score thresholds and survival durations, we found that PPI was most accurate for predicting survival of <3 weeks and <6 weeks. Survival prediction of <3 weeks was most accurate when PPI score>6 (pooled sensitivity = 0.68, 95% CI 0.60–0.75, specificity = 0.80, 95% CI 0.75–0.85). Survival prediction of <6 weeks was most accurate when PPI score>4 (pooled sensitivity = 0.72, 95% CI 0.65–0.78, specificity = 0.74, 95% CI 0.66–0.80). Comparative meta-analyses found that PPI performed similarly to Delirium-Palliative Prognostic Score and Palliative Prognostic Score in predicting <3-week survival, but less accurately in <30-day survival prediction. However, Delirium-Palliative Prognostic Score and Palliative Prognostic Score only provide <30-day survival probabilities, and it is uncertain how this would be helpful for patients and clinicians. PPI also performed similarly to clinician predicted survival in predicting <30-day survival. However, these findings should be interpreted with caution as limited studies were available for comparative meta-analyses. Risk of bias was high for all studies, mainly due to poor reporting of statistical analyses. while there were low applicability concerns for most (38/39) studies. Conclusions: PPI score>6 should be used for <3-week survival prediction, and PPI score>4 for <6-week survival. PPI is easily scored and does not require invasive tests, and thus would be easily implemented in multiple care settings. Given the acceptable accuracy of PPI in predicting <3- and <6-week survival and its objective nature, it could be used to cross-check clinician predicted survival especially when clinicians have doubts about their own judgement, or when clinician estimates seem to be less reliable. Future studies should adhere to the reporting guidelines and provide comprehensive analyses of PPI model performance.

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Utility of Palliative Prognostic Index in Predicting Survival Outcomes in Patients With Hematological Malignancies in the Acute Ward Setting

Cited by 7 publications

References 30 publications

Outcomes of Patients With Hematologic Malignancies Who Received Inpatient Palliative Care Consultation

Outcomes of Patients With Hematologic Malignancies Who Received Inpatient Palliative Care Consultation

Factors Associated With Survival in Patients With End-of-Life Hematological Malignancies Who Received Chemotherapy: A Retrospective Single-Institution Study

Performance of the Palliative Prognostic Index for cancer patients: A systematic review and meta-analysis

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