Evidence map›Paper›PMID 36952150›Full record

ArticleAnnals of surgical oncology2023

The Application of Artificial Intelligence to Investigate Long-Term Outcomes and Assess Optimal Margin Width in Hepatectomy for Intrahepatic Cholangiocarcinoma.

Laura Alaimo, Zorays Moazzam, Yutaka Endo, Henrique A Lima, Swatika P Butey, Andrea Ruzzenente, Alfredo Guglielmi, Luca Aldrighetti, Matthew Weiss, Todd W Bauer and 16 more

Abstract read
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In one paragraph

Article in Annals of surgical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Application of AI on cholangiocarcinoma.Frontiers in oncology · 2024
    Review
  7. Article
  8. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

26 authors.

Laura AlaimoDivision of Surgical Oncology, Wexner Medical Center, James Comprehensive Cancer Center, Department of Surgery, The Ohio State University, 395 West 12th Avenue, Suite 670, Columbus, OH, USA.
Zorays MoazzamDivision of Surgical Oncology, Wexner Medical Center, James Comprehensive Cancer Center, Department of Surgery, The Ohio State University, 395 West 12th Avenue, Suite 670, Columbus, OH, USA.
Yutaka EndoDivision of Surgical Oncology, Wexner Medical Center, James Comprehensive Cancer Center, Department of Surgery, The Ohio State University, 395 West 12th Avenue, Suite 670, Columbus, OH, USA.
Henrique A LimaDivision of Surgical Oncology, Wexner Medical Center, James Comprehensive Cancer Center, Department of Surgery, The Ohio State University, 395 West 12th Avenue, Suite 670, Columbus, OH, USA.
Swatika P ButeyDivision of Surgical Oncology, Wexner Medical Center, James Comprehensive Cancer Center, Department of Surgery, The Ohio State University, 395 West 12th Avenue, Suite 670, Columbus, OH, USA.
Andrea RuzzenenteDepartment of Surgery, University of Verona, Verona, Italy.
Alfredo GuglielmiDepartment of Surgery, University of Verona, Verona, Italy.
Luca AldrighettiDepartment of Surgery, Ospedale San Raffaele, Milan, Italy.
Matthew WeissDepartment of Surgery, Johns Hopkins Hospital, Baltimore, MD, USA.
Todd W BauerDepartment of Surgery, University of Virginia, Charlottesville, VA, USA.
Sorin AlexandrescuDepartment of Surgery, Fundeni Clinical Institute, Bucharest, Romania.
George A PoultsidesDepartment of Surgery, Stanford University, Stanford, CA, USA.
Shishir K MaithelDepartment of Surgery, Emory University, Atlanta, GA, USA.
Hugo P MarquesDepartment of Surgery, Curry Cabral Hospital, Lisbon, Portugal.
Guillaume MartelDepartment of Surgery, University of Ottawa, Ottawa, ON, Canada.
Carlo PulitanoDepartment of Surgery, Royal Prince Alfred Hospital, University of Sydney, Sydney, NSW, Australia.
Feng ShenDepartment of Surgery, Eastern Hepatobiliary Surgery Hospital, Shanghai, China.
François CauchyDepartment of Hepatobiliopancreatic Surgery and Liver Transplantation, AP-HP, Beaujon Hospital, Clichy, France.
Bas Groot KoerkampDepartment of Surgery, Erasmus University Medical Centre, Rotterdam, The Netherlands.
Itaru EndoDepartment of Gastroenterological Surgery, Yokohama City University School of Medicine, Yokohama, Japan.
Minoru KitagoDepartment of Surgery, Keio University, Tokyo, Japan.
Alex KimDivision of Surgical Oncology, Wexner Medical Center, James Comprehensive Cancer Center, Department of Surgery, The Ohio State University, 395 West 12th Avenue, Suite 670, Columbus, OH, USA.
Aslam EjazDivision of Surgical Oncology, Wexner Medical Center, James Comprehensive Cancer Center, Department of Surgery, The Ohio State University, 395 West 12th Avenue, Suite 670, Columbus, OH, USA.
Joal BeaneDivision of Surgical Oncology, Wexner Medical Center, James Comprehensive Cancer Center, Department of Surgery, The Ohio State University, 395 West 12th Avenue, Suite 670, Columbus, OH, USA.
Jordan CloydDivision of Surgical Oncology, Wexner Medical Center, James Comprehensive Cancer Center, Department of Surgery, The Ohio State University, 395 West 12th Avenue, Suite 670, Columbus, OH, USA.
Timothy M PawlikDivision of Surgical Oncology, Wexner Medical Center, James Comprehensive Cancer Center, Department of Surgery, The Ohio State University, 395 West 12th Avenue, Suite 670, Columbus, OH, USA. Tim.Pawlik@osumc.edu.ORCID http://orcid.org/0000-0002-7994-9870

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIntrahepatic cholangiocarcinoma (ICC) is associated with poor long-term outcomes, and limited evidence exists on optimal resection margin width. This study used artificial intelligence to investigate long-term outcomes and optimal margin width in hepatectomy for ICC.

methodsThe study enrolled patients who underwent curative-intent resection for ICC between 1990 and 2020. The optimal survival tree (OST) was used to investigate overall (OS) and recurrence-free survival (RFS). An optimal policy tree (OPT) assigned treatment recommendations based on random forest (RF) counterfactual survival probabilities associated with each possible margin width between 0 and 20 mm.

resultsAmong 600 patients, the median resection margin was 4 mm (interquartile range [IQR], 2-10). Overall, 379 (63.2 %) patients experienced recurrence with a 5-year RFS of 28.3 % and a 5-year OS of 38.7 %. The OST identified five subgroups of patients with different OS rates based on tumor size, a carbohydrate antigen 19-9 [CA19-9] level higher than 200 U/mL, nodal status, margin width, and age (area under the curve [AUC]: training, 0.81; testing, 0.69). The patients with tumors smaller than 4.8 cm and a margin width of 2.5 mm or greater had a relative increase in 5-year OS of 37 % compared with the entire cohort. The OST for RFS estimated a 46 % improvement in the 5-year RFS for the patients younger than 60 years who had small (<4.8 cm) well- or moderately differentiated tumors without microvascular invasion. The OPT suggested five optimal margin widths to maximize the 5-year OS for the subgroups of patients based on age, tumor size, extent of hepatectomy, and CA19-9 levels.

conclusionsArtificial intelligence OST identified subgroups within ICC relative to long-term outcomes. Although tumor biology dictated prognosis, the OPT suggested that different margin widths based on patient and disease characteristics may optimize ICC long-term survival.

Indexed as

Bile Duct NeoplasmsCholangiocarcinomaArtificial IntelligenceBile Ducts, IntrahepaticCA-19-9 AntigenHepatectomyHumansMargins of ExcisionPrognosisRetrospective StudiesCA-19-9 Antigen

Identifiers

PMID36952150

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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.