Lung Immune Prognostic Index Meta-Analysis for Urological Cancers
by Zhaojie Lyu·Updated 3mo ago
28.3 KB1files
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Description
13 studies comprising 19 cohorts and 5,304 patients were included in this systematic review and meta-analysis. The work quantifies the association between Lung Immune Prognostic Index categories and survival outcomes in renal cell, urothelial, and prostate cancers. It provides pooled hazard ratios for overall and progression-free survival across good, intermediate, and poor LIPI groups.
Use Cases
Validate the prognostic value of LIPI categories (good/intermediate/poor) for overall survival in urological cancer cohorts.
Compare hazard ratio estimates for progression-free survival between intermediate and poor LIPI groups across different tumor types.
Assess the consistency of LIPI's prognostic gradient in immune checkpoint inhibitor-treated patient subgroups.
Reconstruct or verify hazard ratios using the described pseudo-individual patient data methodology from Kaplan-Meier curves.
Strengths
Analysis aggregates data from 13 studies representing 5,304 patients, providing a substantial evidence base.
Follows PRISMA guidelines and used a prospectively registered protocol (CRD420251235082), ensuring methodological rigor.
Reports specific pooled hazard ratios with confidence intervals for both overall and progression-free survival outcomes.
Limitations
The dataset is a 28.3 KB DOCX file containing summarized meta-analysis results, not the underlying patient-level data.
Scope is limited to the specific research question of LIPI's prognostic value in three urological cancers.
Relies on reconstructed hazard ratios from Kaplan-Meier curves for some studies, introducing potential estimation error.
Provenance
Source
Systematic review and meta-analysis conducted by author Zhaojie Lyu, sourced from figshare.
Collection Method
Literature search of PubMed, Embase, and Cochrane Library; data extraction and pooling using random-effects models with REML and Hartung-Knapp adjustment.
Time Range
Studies included were searched through October 2025.
Freshness
Literature search was conducted through October 2025, and the dataset was last updated in March 2026.
Geography
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Data is presented in a summarized format within a DOCX document; users seeking raw study data or individual patient records must consult the original publications.