Evidence map›Paper›PMID 37454351›Full record

SynthesisArchives of gynecology and obstetrics2024

The role of L1CAM as predictor of poor prognosis in stage I endometrial cancer: a systematic review and meta-analysis.

Andrea Giannini, Ottavia D'Oria, Giacomo Corrado, Valentina Bruno, Isabella Sperduti, Giorgio Bogani, Antonio Simone Laganà, Vito Chiantera, Donatella Caserta, Enrico Vizza

Abstract readMeta-AnalysisSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Archives of gynecology and obstetrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 1 pooled it
12.4field-weighted citation impact, top 1% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

33 citing papers in PubMed, 1 synthesis or guideline pooled it, 42 citations in OpenAlex.

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  12. UnveilingTranslational cancer research · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 5 institutions in 1 country.

Andrea Giannini *Department of Medical and Surgical Sciences and Translational Medicine, PhD Course in "Translational Medicine and Oncology", Sapienza University, Rome, Italy. andrea.giannini@uniroma1.it.ORCID 0000-0002-4388-0082
Ottavia D'Oria *Department of Medical and Surgical Sciences and Translational Medicine, PhD Course in "Translational Medicine and Oncology", Sapienza University, Rome, Italy.
Giacomo CorradoDipartimento Scienze della Salute della Donna, del Bambino, e di Sanità Pubblica, Ginecologia Oncologica, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.
Valentina BrunoGynecologic Oncology Unit, Department of Experimental Clinical Oncology, IRCSS-Regina Elena National Cancer Unit Institute, Rome, Italy.
Isabella SperdutiScientific Direction, IRCCS "Regina Elena" National Cancer Institute, Rome, Italy.
Giorgio BoganiDepartment of Maternal and Child Health and Urological Sciences, Sapienza University of Rome, Policlinico Umberto I, Rome, Italy.
Antonio Simone LaganàUnit of Gynecologic Oncology, ARNAS "Civico - Di Cristina - Benfratelli", Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties (PROMISE), University of Palermo, Palermo, Italy.
Vito ChianteraUnit of Gynecologic Oncology, ARNAS "Civico - Di Cristina - Benfratelli", Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties (PROMISE), University of Palermo, Palermo, Italy.
Donatella CasertaGynecology Division, Department of Medical and Surgical Sciences and Translational Medicine, Sant'Andrea University Hospital, Sapienza University of Rome, Via di Grottarossa 1035, 00189, Rome, Italy.
Enrico VizzaGynecologic Oncology Unit, Department of Experimental Clinical Oncology, IRCSS-Regina Elena National Cancer Unit Institute, Rome, Italy.
University of Palermo · ITAgostino Gemelli University Polyclinic · ITIstituti di Ricovero e Cura a Carattere Scientifico · ITPoliclinico Umberto I · ITSapienza University of Rome · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionMolecular and genomic profiling in endometrial cancer is increasing popularity. L1 cell adhesion molecule (L1CAM) is frequently mutated in endometrial cancer. In this paper, we aim to evaluate the prognostic role of L1CAM in patients with stage I endometrial cancer.

methodsWe performed a systematic review and meta-analysis searching in PubMed (MEDLINE), EMBASE, and Web of Science database to identify studies reporting the expression of L1CAM in endometrial cancer. The primary endpoint measure was to assess and evaluate the impact of L1CAM on survival outcomes. This study was performed according to the Preferred Reporting Items for Systematic review and Meta-Analysis Protocols (PRISMA-P) statement.

resultsFive studies were included. The pooled results suggested that L1CAM expression influences survival outcomes in stage I endometrial cancer. High L1CAM expression correlated with worse disease-free survival (HR 4.11, 95% CI 1.02-16.59, p = 0.047) and overall survival (HR 3.62, 95% CI 1.32-9.31, p = 0.012). High L1CAM level was also associated with a more aggressive FIGO grade and with older age.

conclusionThis systematic review supported that L1CAM have a prognostic role in stage I endometrial cancer, thus providing a potential useful tool for tailoring the need of adjuvant therapy.

Indexed as

Endometrial NeoplasmsNeural Cell Adhesion Molecule L1Biomarkers, TumorFemaleHumansNeoplasm StagingPrognosisBiomarkers, TumorNeural Cell Adhesion Molecule L1BiomarkersEndometrial cancerL1 cell adhesion molecule (L1CAM)Molecular profilingTarget therapies

Identifiers

PMID37454351
OpenAlexW4384471039

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.