Evidence map›Paper›PMID 41121083›Full record

Observational studyBMC cancer2025

Real-world evidence in localized and locally advanced prostate cancer: applying artificial intelligence to electronic health records.

José Pablo Maroto, Javier Puente, Antonio Conde Moreno, Álvaro Juárez, Beatriz Garcillán, José Miguel Calderón, Jacobo Muñoz Del Toro, Juan Luis Valdivieso, María López-Menduiña, Eduard Sarró and 1 more

Abstract readObservational Study
In one paragraph

Observational study in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

11 authors.

José Pablo MarotoDepartment of Medical Oncology, Hospital de La Santa Creu I Sant Pau, Barcelona, Spain.
Javier PuenteDepartment of Medical Oncology, Hospital Clínico San Carlos, Madrid, Spain.
Antonio Conde MorenoDepartment Of Radiation Oncology, Hospital Universitario La Fe, Valencia, Spain.
Álvaro JuárezDepartment of Urology, Hospital Universitario de Jerez, Jerez, Spain.
Beatriz GarcillánMedical Affairs Department, Janssen-Cilag S.A. a Johnson & Johnson Company, Madrid, Spain. bgarcill@its.jnj.com.
José Miguel CalderónMedical Affairs Department, Janssen-Cilag S.A. a Johnson & Johnson Company, Madrid, Spain.
Jacobo Muñoz Del ToroMedical Affairs Department, Janssen-Cilag S.A. a Johnson & Johnson Company, Madrid, Spain.
Juan Luis ValdiviesoSavana Research S.L., Madrid, Spain.
María López-MenduiñaSavana Research S.L., Madrid, Spain.
Eduard SarróSavana Research S.L., Madrid, Spain.
Antonio AlcarazDepartment of Urology, Hospital Clinic, Barcelona, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo provide real-world evidence of the clinical characteristics and outcomes of localized and locally advanced prostate cancer patients (LPC/LAPC). MATERIALS &

methodsObservational and retrospective analysis using secondary data from electronic health records (EHR) of prostate cancer (PC) patients in eight Spanish hospitals (2014–2018). Data was extracted and analyzed using EHRead® technology, based on natural language processing and machine learning. LPC/LAPC patients were included and stratified by risk and by first treatment received.

resultsTwenty-two thousand one hundred sixty-six PC patients were identified,14,434 (65.1%) were classified as LPC/LAPC. Among them, 5,331 incident patients with sufficient data were selected for outcome analysis (real world overall survival [rwOS], metastasis and event free survival [MFS, EFS]) and were followed for a median time of 2.3 years. 36.5% were classified as LPC intermediate risk (IR), 26.0% LPC high risk (HR), 7.3% LPC low risk (LR), 5.9% LAPC, and 24.2% unknown risk. First treatment received was radiotherapy (RT) in 40.7%, radical prostatectomy (RP) in 37.1%, active surveillance (AS)/watchful waiting (WW) in 6.4%, brachytherapy (BT) in 4.2%, and androgen deprivation therapy monotherapy (ADT only) in 3.3%. rwOS and MFS worsened as risk increased. Patients treated with ADT only presented the worst baseline characteristics, showing limited clinical outcomes. The 36-month rwOS was 91% for LAPC patients, 93% for HR-LPC, 97% for IR-LPC, and 98% for LR-LPC.

conclusionsDespite using treatment with curative intent, patients experienced oncological events within a median of less than three years post-diagnosis. Our findings emphasize the need for risk stratification, and proactive strategies to improve clinical outcomes.

Indexed as

Artificial IntelligenceElectronic Health RecordsProstatic NeoplasmsAgedHumansMachine LearningMaleMiddle AgedProstatectomyRetrospective StudiesSpainElectronic health recordsLocalized and locally advanced prostate cancerMachine learningNatural language processingProstate cancer

Identifiers

PMID41121083
PMCPMC12539219

What OpenQuestion holds

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Registered trials

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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.