Usefulness of the Palliative Prognostic Index in patients with lung cancer

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

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.

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

PURPOSE

The Palliative Prognostic Index (PPI) was developed to improve survival prediction for advanced cancer patients. However, there is limited data about the PPI application in a real-world scenario. This study aimed to assess the accuracy of PPI > 6 in predicting survival of cancer inpatients.

METHODS

A prospective observational cohort in an inpatient palliative care service at a tertiary hospital in São Paulo-SP, Brazil, between May 2011 and December 2018.

RESULTS

We included 1,376 critically ill cancer inpatients. Patients were divided into three PPI subgroups: PPI ≤ 4, PPI 4-6, and PPI ≥ 6. Their respective medium overall survival values were 44 days (95% confidence interval [CI] 35.52-52.47), 20 days (95% CI 15.40-24.59), and 8 days (95% CI 7.02-8.98), (p < 0.001). PPI ≥ 6 predicted survival of <3 weeks with a positive predictive value (PPV) of 72% and an negative predictive value (NPV) of 68% (sensitivity 67%, specificity 72%). PPI > 4 predicted survival of <6 weeks with a PPV of 88% and an NPV of 36% (sensitivity 74%, specificity 59%). When PPI was <4, the mortality rate over 3 weeks was 39% with a relative risk (RR) of 0.15 (95% CI 0.11-0.20; p < 0.001), and the 6-week mortality rate was 63% with a RR of 0.18 (95% CI 0.13-0.25; p < 0.001) compared to PPI ≥ 4.

CONCLUSIONS

PPI was a good discriminator of survival among critically ill cancer inpatients and could assist in hospital discharge decision. PPI may help healthcare policymakers and professionals in offering high-quality palliative care to patients.

Relationship between Patient Characteristics and the Timing of Provision of Explanation about DNAR to Patients with Advanced Lung Cancer

Objective The aim of the present study was to analyze the relationship between the patient characteristics and the timing of provision of an explanation about "Do Not Attempt Resuscitation (DNAR)" by attending physicians to advanced lung cancer patients. Methods We conducted a retrospective analysis of patients with advanced or postoperative recurrent lung cancer in whom systemic therapy was initiated between 2015 and 2016. Results The data of a total of 74 patients with lung cancer, including 59 patients with non-small cell lung cancer and 15 with small cell lung cancer were analyzed. The median overall survival of the patients was 10.0 months. Records of the explanation about DNAR by the physicians were available for 57 of the 74 (77.0%) patients. For 48 (64.9%) patients, the explanation was provided after the discontinuation of anticancer treatment, and for 9 (12.2%) patients, it was provided during the course of anticancer treatment. The provision of an explanation about DNAR during the course of treatment was associated with a poor performance status at the start of treatment (p=0.028), the tumor histology (p=0.037), the presence of driver gene mutation in the tumor (p=0.029), and shorter survival after the discontinuation of anticancer treatment (p<0.001). Conclusion The results suggested that the timing of provision of an explanation about DNAR was associated with patient characteristics and the predicted prognosis.

PTBP3 promotes migration of non-small cell lung cancer through regulating E-cadherin in EMT signaling pathway

Background

Human polypyrimidine tract binding protein 3 (PTBP3), which belongs to the PTB family, demonstrate a significant tumorigenic capability in a variety of malignancies. However, the correlation between PTBP3 expression and pathogenesis of non-small cell lung cancer (NSCLC) remains little known. The design of the study attempts to examine the role of PTBP3 in the pathogenesis and prognosis of NSCLC.

Methods

Our study conducted an investigation on the PTBP3 expression in human NSCLC tissues and a comprehensive analysis of the associations between three factors, involving the PTBP3 expression, clinicopathological features, and patient’s survival. Additionally, we also explored the role of PTBP3 expression in the proliferation and invasion of cancer cells.

Results

The mining of The Cancer Genome Atlas (TCGA) database, western blotting and immunohistochemistry analyses showed significantly up-regulation of PTBP3 in NSCLC tissues than in normal tissues. Although overexpress or knockdown PTBP3 expression had no significant effect on proliferation of selected cell line, it could promotes migration of NSCLC cells via regulating E-cadherin in epithelial–mesenchymal transition (EMT) signaling pathway. Moreover, in the univariate analysis, the PTBP3-high is markedly related to poor overall survival results where hazard ratio (HR): 1.55; 95% confidence interval (95% CI): 1.87–2.01; p = 0.0001. Also, according to the multivariate analysis, an independent prognostic factor among NSCLC patients is the PTBP3 with an HR of 1.42 (CI: 1.09–1.9; p = 0.011). To explore potential signaling pathways, we used the TCGA dataset and performed Gene Set Enrichment Analysis (GSEA). Moreover, its expression in NSCLC was related to Tumor differentiation, lymph node metastasis, distant metastasis status and poor prognosis. Beside, by changing the expression of PTBP3 in selected cell lines, we found that overexpress or knockdown PTBP3 expression had no significant effect on proliferation, however it regulated migration possibly by EMT signaling.

Conclusions

Collectively, our findings suggested that PTBP3 contributed to the progression of NSCLC and might serve as a potential target for anti-cancer therapy.

The application of the palliative prognostic index in predicting the life expectancy of patients in palliative care: a systematic review and meta-analysis

BACKGROUND

The palliative prognostic index (PPI) is a commonly used tool to predict the life expectancy in palliative care patients. However, there is no universal cutoff, and the accuracy of different cutoffs varies. Therefore, we conducted this meta-analysis to explore the validity and accuracy of different PPI scores for different survival time in palliative care setting.

METHODS

PubMed, Embase, Cochrane, Scopus and Chinese CNKI databases were searched to identify studies using the PPI as a prognostic tool to predict survival time in palliative care. We calculated pooled hazard ratios (HRs) with corresponding 95% confidence intervals (CIs), and subgroup analyses were also conducted by different cutoffs. After extracting data, we estimated the pooled sensitivity, specificity, positive predictive value, and negative predictive value.

RESULTS

We identified 15 studies with 7455 assessments. Seven of these studies were synthesized for a combined HR. The pooled HR was 1.94 (95% CI 1.54-2.44) when cutoffs were 2 and 4, and 2.34 (95% CI 1.50-3.66) when cutoffs were 4 and 6. Of all the studies, 13 studies reported their accuracy, of which four studies were assessed by meta-analysis. The sensitivity of the PPI for 3-week survival ranged from 51 to 92% and specificity ranged from 60.0 to 94.0%, respectively. The sensitivity and specificity of the PPI for 6-week survival were from 46.0 to 89.1% and from 51.7 to 84.4%, respectively. The pooled sensitivity and specificity of the PPI for 3-week survival were 68% (6 as cutoff) and 76% (6 as cutoff), respectively. As for 6-week survival prediction, the pooled sensitivity and specificity were 68% (4 as cutoff) and 82% (4 as cutoff), respectively.

CONCLUSION

The PPI is a useful prognosticator of life expectancy of patients in palliative care, especially for patients with short survival time. However, there were no universal cutoff, and the predicted life span varies. Our data eliminated that using 4 and 6 as cutoffs can better predict the patients' survival time for 3 or 6 weeks. Due to small number of studies and poor qualities of them, result may alter as more studies with better quality are enrolled in the future.

The Prognostic Effect of MAC30 Expression on Patients With Non-Small Cell Lung Cancer Receiving Adjuvant Chemotherapy

The purpose of this study was to examine the MAC30 expression in non-small cell lung cancer and to evaluate its prognostic value on therapeutic response in patients with non-small cell lung cancer receiving postoperative chemotherapy. Among a total of 218 retrospective Chinese patients with non-small cell lung cancer, 164 patients receiving adjuvant chemotherapy were enrolled in this study. Real-time polymerase chain reaction was performed to confirm the expression of MAC30 messenger RNA in 32 cases of non-small cell lung cancer tumors with the corresponding nontumor lung tissues. The MAC30 protein expression in all specimens was analyzed by immunohistochemical staining. Moreover, we assessed the correlation of MAC30 expression with clinicopathological features, therapeutic response, and survival of patients. Here, we observed the increased expression of MAC30 messenger RNA in patients with non-small cell lung cancer compared to those in control samples. The overexpression of MAC30 was strongly associated with poor tumor differentiation, high tumor-node-metastasis stage, and lymph node metastasis. In addition, we observed that patients with increased MAC30 expression showed gloomy overall survival and disease-free survival. A multivariate analysis explicated that higher MAC30 expression was a valuable independent prognostic factor of poorer tumor differentiation, shorter overall survival, and disease-free survival in patients receiving chemotherapy. MAC30 could be a useful biomarker of tumor differentiation and outcome of patients with non-small cell lung cancer. Overexpression of MAC30 predicts a worse tumor differentiated stage and prognosis in patients with non-small cell lung cancer receiving adjuvant chemotherapy.