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Large-scale Models of Esophageal Cancer and Related Research (DeepDT)

7. juni 2026 opdateret af: The First Affiliated Hospital of Henan University of Science and Technology

Clinical Application Research of AI-Based Large Models for Early Screening, Diagnosis, Treatment, and Prognosis Assessment of Esophageal Cancer

The goal of this observational study is to learn about the clinical utility of an artificial intelligence (AI) large language model in patients undergoing screening, diagnosis, treatment, and prognosis assessment for esophageal cancer. The main question it aims to answer is:

Does the AI model improve early detection rate, diagnostic accuracy, treatment personalization, and prognostic prediction for esophageal cancer compared to standard care? Participants already receiving routine esophageal cancer management (including endoscopy, imaging, pathology, and clinical follow-up) as part of their regular medical care will have their de-identified data processed by the AI model; researchers will compare model-based recommendations and outcomes with standard care benchmarks over 3 years.

Last updated on Oct 31, 2027

Studieoversigt

Status

Tilmelding efter invitation

Betingelser

Intervention / Behandling

Undersøgelsestype

Observationel

Tilmelding (Anslået)

12000

Kontakter og lokationer

Dette afsnit indeholder kontaktoplysninger for dem, der udfører undersøgelsen, og oplysninger om, hvor denne undersøgelse udføres.

Studiesteder

  • Kina
    • Henan
      • Anyang, Henan, Kina, 455000
        • AnYang Tumor Hospital
      • Luoyang, Henan, Kina, 471000
        • The First Affiliated Hospital of Henan University of Science & Technology
      • Nanyang, Henan, Kina, 473000
        • Nanyang Central Hospital Medical Ethics Committee

Deltagelseskriterier

Forskere leder efter personer, der passer til en bestemt beskrivelse, kaldet berettigelseskriterier. Nogle eksempler på disse kriterier er en persons generelle helbredstilstand eller tidligere behandlinger.

Berettigelseskriterier

Aldre berettiget til at studere

  • Voksen
  • Ældre voksen

Tager imod sunde frivillige

Ingen

Prøveudtagningsmetode

Ikke-sandsynlighedsprøve

Studiebefolkning

The study population comprises patients receiving routine esophageal cancer management at participating healthcare institutions, including those undergoing screening (e.g., endoscopy), diagnosis (imaging, pathology), treatment (endoscopic resection, surgery, chemotherapy, radiotherapy), and prognostic follow-up. Inclusion criteria: age ≥18 years, suspected or confirmed esophageal cancer, and available complete clinical data (endoscopy, imaging, pathology, and follow-up records). Exclusion criteria: incomplete data or refusal to use medical records. The population spans early to advanced stages to evaluate the AI model across the full disease spectrum.

Beskrivelse

Inclusion Criteria:

  • 1. Aged 18 years or older. 2. Individuals with normal findings or inflammatory changes: endoscopic or pathological reports indicating "no significant abnormalities detected" or changes consistent with inflammation.

    3. Individuals with benign lesions: pathological reports specifying "absence of tumor cells" or a diagnosis consistent with benign lesions.

    4. Individuals with precancerous lesions: pathological reports with a definitive diagnosis of Low-grade Intraepithelial Neoplasia (LGIN) or High-grade Intraepithelial Neoplasia (HGIN).

    5. Individuals with malignant tumors: pathological reports confirming a diagnosis of esophageal squamous cell carcinoma or esophageal adenocarcinoma.

Exclusion Criteria:

  • 1. Diagnostically uncertain: Lack of definitive pathological evidence, or with doubtful clinical diagnosis.

    2. Poor data quality: Low-quality key imaging data (endoscopy, CT) that is unsuitable for analysis (e.g., severe artifacts, missing images).

    3. Severe missingness of key clinical or follow-up data (missing rate > 20%). 4. Confounding by other malignancies: Presence of other active malignant tumors other than esophageal cancer within 5 years prior to enrollment.

    5. Loss to follow-up: Failure to obtain key survival or recurrence follow-up information in the retrospective cohort.

Studieplan

Dette afsnit indeholder detaljer om studieplanen, herunder hvordan undersøgelsen er designet, og hvad undersøgelsen måler.

Hvordan er undersøgelsen tilrettelagt?

Design detaljer

Kohorter og interventioner

Gruppe / kohorte
Intervention / Behandling
Single cohort
Patients receiving routine esophageal cancer management (including endoscopy, imaging, pathology, and clinical follow-up) as part of their regular medical care. De-identified data from these participants will be processed by an AI large language model, and model-based recommendations will be compared with standard care benchmarks over 3 years.
Andet: Observational study; no assigned intervention. Participants receive routine esophageal cancer management (endoscopy, imaging, pathology, clinical follow-up) as standard care.
Routine esophageal cancer management including endoscopy, imaging, pathology, and clinical follow-up as per standard clinical practice. No additional, experimental, or assigned intervention is administered. The AI large language model processes de-identified data from routine care for comparative analysis against standard care benchmarks over 3 years.

Hvad måler undersøgelsen?

Primære resultatmål

Resultatmål
Tidsramme
Area under the ROC curve (AUC) of the multimodal model for diagnosing esophageal cancer, calculated by ROC analysis using pathological biopsy as the gold standard, based on 5-fold cross-validation on the internal validation set.
Tidsramme: Up to 3 years
Up to 3 years
Overall accuracy (proportion of correct classifications) of the multimodal model for diagnosing esophageal cancer, derived from the confusion matrix of the model's predictions on the internal validation set, with pathological biopsy as the gold standard.
Tidsramme: Up to 3 years
Up to 3 years
Concordance index (C-index) of the multimodal model for predicting overall survival and progression-free survival, derived from Cox proportional hazards model on time-to-event data.
Tidsramme: Up to 3 years
Up to 3 years

Samarbejdspartnere og efterforskere

Det er her, du vil finde personer og organisationer, der er involveret i denne undersøgelse.

Sponsor

The First Affiliated Hospital of Henan University of Science and Technology

Datoer for undersøgelser

Disse datoer sporer fremskridtene for indsendelser af undersøgelsesrekord og resumeresultater til ClinicalTrials.gov. Studieregistreringer og rapporterede resultater gennemgås af National Library of Medicine (NLM) for at sikre, at de opfylder specifikke kvalitetskontrolstandarder, før de offentliggøres på den offentlige hjemmeside.

Studer store datoer

Studiestart (Faktiske)

15. maj 2026

Primær færdiggørelse (Anslået)

31. oktober 2027

Studieafslutning (Anslået)

31. oktober 2027

Datoer for studieregistrering

Først indsendt

1. juni 2026

Først indsendt, der opfyldte QC-kriterier

7. juni 2026

Først opslået (Faktiske)

11. juni 2026

Opdateringer af undersøgelsesjournaler

Sidste opdatering sendt (Faktiske)

11. juni 2026

Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier

7. juni 2026

Sidst verificeret

1. juni 2026

Mere information

Begreber relateret til denne undersøgelse

Yderligere relevante MeSH-vilkår

Andre undersøgelses-id-numre

  • 2025-0697

Plan for individuelle deltagerdata (IPD)

Planlægger du at dele individuelle deltagerdata (IPD)?

INGEN

Lægemiddel- og udstyrsoplysninger, undersøgelsesdokumenter

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Studerer et amerikansk FDA-reguleret enhedsprodukt

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Disse oplysninger blev hentet direkte fra webstedet clinicaltrials.gov uden ændringer. Hvis du har nogen anmodninger om at ændre, fjerne eller opdatere dine undersøgelsesoplysninger, bedes du kontakte register@clinicaltrials.gov. Så snart en ændring er implementeret på clinicaltrials.gov, vil denne også blive opdateret automatisk på vores hjemmeside .

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