SynthesisPharmacoepidemiology and drug safety2025
Diagnostic Performance of Prostate Cancer Disease-Specific Phenotypes Identified Using Real-World Databases: A Systematic Review.
Synthesis in Pharmacoepidemiology and drug safety, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Diagnostic Performance of Prostate Cancer Disease-Specific Phenotypes Identified Using Real-World Databases: A Systematic Review.Pharmacoepidemiology and drug safety · 2025Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundResearch using real-world databases (RWD) often requires the development of computable phenotypes based on clinical reasoning-based algorithms or prediction models with validation through a reference standard such as chart review. While there are studies reporting different phenotypes for key prostate cancer (PC) disease or outcomes, these have not been summarized systematically.
objectivesTo conduct a systematic review (SR) to summarize validation statistics on PC-specific phenotypes, including metastasis, biochemical recurrence (BCR), castration-resistant prostate cancer (CRPC), hormone-sensitive prostate cancer (HSPC), progression-free survival, and performance status.
methodsWe conducted a SR in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis of Diagnostic Test Accuracy Studies guidelines. We systematically searched PubMed/Medline and EMBASE for studies reporting algorithms and prediction models for PC phenotypes based on structured RWD published between 2012 and 2024. A summary of algorithms and prediction models, along with their respective estimates of diagnostic accuracy compared to reference standards and/or measures of uncertainty, was provided. An area under the curve (AUC) > 0.7 was considered an acceptable phenotype.
resultsOut of 7427 retrieved citations, 29 unique retrospective studies (31 citations) were included. Both claims-based codes and prediction model-based classification for any metastasis and bone metastases had an acceptable performance with high AUC (0.88 and > 0.7, respectively) and high specificity (above 90%) with a few having moderate sensitivity (60% to 100%). The prediction model-based BCR classification had acceptable performance (AUC > 0.7); however, claims-based BCR had moderate performance statistics with sensitivity in the range of 3%-19% and specificity in the range of 83%-98%. One claims-based algorithm for metastatic CRPC had high sensitivity (77%) and specificity (100%). Studies for mHSPC were based on clinical reasoning without assessing their diagnostic accuracy. Claims-based algorithms for performance status had at least 75% sensitivity and relatively high specificity.
conclusionsOur SR highlights the acceptable accuracy of computable phenotypes for PC, including (bone) metastasis, BCR, and performance status within RWD. Further validation studies are needed for RWD-based phenotypes to account for changes in therapeutic options in PC.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.