Evidence map›Paper›PMID 39076326›Full record

ArticleReviews in cardiovascular medicine2024

Studying the Outcomes in Patients with Tricuspid Regurgitation Treated with Valve Repair or Valve Replacement: Interpreting the Survival Pattern on The Long Term by Application of Artificial Intelligence Methods.

Andrea Messori, Sabrina Trippoli, Maria Rita Romeo, Valeria Fadda, Melania Rivano, Lorenzo Di Spazio

Abstract read
In one paragraph

Article in Reviews in cardiovascular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Andrea MessoriHTA Unit, Regione Toscana, Regional Health Service, 50139 Firenze, Italy.
Sabrina TrippoliHTA Unit, Regione Toscana, Regional Health Service, 50139 Firenze, Italy.
Maria Rita RomeoOspedale del Cuore, Fondazione Monasterio, Regional Health Service, 54100 Massa, Italy.
Valeria FaddaESTAR Toscana, Regional Health Service, 50135 Firenze, Italy.
Melania RivanoHospital Pharmacy Department, R. Binaghi, 09126 Cagliari, Italy.
Lorenzo Di SpazioHospital Pharmacy Department, S. Chiara Trento Hospital, Azienda Provinciale per i Servizi Sanitari (APSS), 38122 Trento, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The reconstruction of individual patient data from published Kaplan-Meier survival curves is a new technique (often denoted as the IPDfromKM method) for studying efficacy in cases where multiple trials are available, and the endpoint is long-term mortality. In patients with tricuspid regurgitation, both valve repair and valve replacement have been proposed to improve prognosis; 6 controlled clinical trials (CTs) have been conducted to compare the two therapeutic options mentioned above. The objective of our analysis was to study these six trials through the application of the IPDfromKM method. Methods: In the present report, we applied the IPDfromKM method to carry out a pooled analysis of these 6 CTs to investigate the effectiveness of valve repair vs valve replacement and to assess the between-study heterogeneity from this clinical material. After reconstructing individual patient data from these 6 trials, patients treated with valve repair were pooled together and their Kaplan-Meier curve was generated. Likewise, patients treated with valve replacement were pooled together and their Kaplan-Meier curve was generated. Finally, these two curves were compared by standard survival statistics. The hazard ratio (HR) was determined; death from any cause was the endpoint. Results: These 6 CTs included a total of 552 patients; in each of these CTs, the patient group treated with valve repair was compared with another group treated with valve replacement. Our statistical results showed a significantly better survival for valve repair compared with valve replacement (HR, 0.6098; 95% confidence intervals (CI), 0.445 to 0.835; Conclusions: Our analysis confirmed the methodological advantages of the IPDfromKM method in the indirect comparative analysis of multiple trials. These advantages include appropriate analysis of censored patients, original assessment of heterogeneity, and graphical presentation of the results, wherein individual patients retain an important role.

Indexed as

artificial intelligenceipdfromkm methodkaplan-meier curvesmeta-analysisreconstructed individual patient data

Identifiers

PMID39076326
PMCPMC11270104

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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.