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 ( = 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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http://dx.doi.org/10.1177/02692163231180657 | DOI Listing |
Front Biosci (Landmark Ed)
January 2025
Department of Cardiothoracic Surgery, The Affiliated Jiangyin Hospital of Nantong University, 214400 Jiangyin, Jiangsu, China.
Background: This study investigates the role of small ubiquitin-like modifier (SUMO)-specific peptidase 5 (SENP5), a key regulator of SUMOylation, in esophageal squamous cell carcinoma (ESCC), a lethal disease, and its underlying molecular mechanisms.
Methods: Differentially expressed genes between ESCC mouse oesophageal cancer tissues and normal tissues were analysed via RNA-seq; among them, SENP5 expression was upregulated, and this gene was selected for further analysis. Immunohistochemistry and western blotting were then used to validate the increased protein level of SENP5 in both mouse and human ESCC samples.
Front Biosci (Landmark Ed)
January 2025
Division of Biochemistry and Molecular Biology, Federal State Budgetary Educational Institution of Higher Education "Siberian State Medical University" of the Ministry of Health of Russia, 634050 Tomsk, Russia.
Background: Over the past five years, the pregnancy rate in assisted reproductive technology (ART) programs in Russia has remained relatively stable. The aim of this study was to assess the distribution of monocyte and macrophage subsets in the blood and follicular fluid of infertile women undergoing assisted reproductive technology.
Methods: The study involved 45 women with a mean age of 35 ± 4.
Front Biosci (Landmark Ed)
January 2025
Department of Hepatobiliary and Pancreatic Surgery, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, 030032 Taiyuan, Shanxi, China.
Since the discovery of the Musashi (MSI) protein, its ability to affect the mitosis of Drosophila progenitor cells has garnered significant interest among scientists. In the following 20 years, it has lived up to expectations. A substantial body of evidence has demonstrated that it is closely related to the development, metastasis, migration, and drug resistance of malignant tumors.
View Article and Find Full Text PDFBr J Hosp Med (Lond)
January 2025
Department of Surgery & Cancer, Imperial College London, London, UK.
Predictive algorithms have myriad potential clinical decision-making implications from prognostic counselling to improving clinical trial efficiency. Large observational (or "real world") cohorts are a common data source for the development and evaluation of such tools. There is significant optimism regarding the benefits and use cases for risk-based care, but there is a notable disparity between the volume of clinical prediction models published and implementation into healthcare systems that drive and realise patient benefit.
View Article and Find Full Text PDFBr J Hosp Med (Lond)
January 2025
Cardio-Oncology Centre of Excellence, Royal Brompton Hospital, London, UK.
The burdens of cardiovascular (CV) diseases and cardiotoxic side effects of cancer treatment in oncology patients are increasing in parallel. The European Society of Cardiology (ESC) 2022 Cardio-Oncology guidelines recommend the use of standardized risk stratification tools to determine the risk of cardiotoxicity associated with different anticancer treatment modalities and the severity of their complications. The use of the Heart Failure Association-International Cardio-Oncology Society (HFA-ICOS) is essential for assessing risk prior to starting cancer treatment, and validation of these methods has been performed in patients receiving anthracyclines, human epidermal receptor 2 (HER2)-targeted therapies and breakpoint cluster region-abelson oncogene locus (BCR-ABL) inhibitors.
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