Evidence map›Paper›PMID 37266808›Full record

ArticleAnnals of surgical oncology2023

Predicting Severe Complications from Cytoreductive Surgery with Hyperthermic Intraperitoneal Chemotherapy: A Data-Driven, Machine Learning Approach to Augment Clinical Judgment.

Mohamed A Adam, Helen Zhou, Jonathan Byrd, Anya L Greenberg, Yvonne M Kelly, Lauren Hall, Heather L Jones, James F Pingpank, Zachary C Lipton, David L Bartlett and 1 more

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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 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 13% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
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  3. Article
  4. Review
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 at 5 institutions in 1 country.

Mohamed A Adam *University of California, San Francisco, CA, USA. Mohamed.Adam@ucsf.edu.
Helen Zhou *Carnegie Mellon University, Pittsburgh, PA, USA.
Jonathan Byrd *Carnegie Mellon University, Pittsburgh, PA, USA.
Anya L GreenbergUniversity of California, San Francisco, CA, USA.
Yvonne M KellyColumbia University, New York, NY, USA.
Lauren HallUniversity of Pittsburgh Medical Center, Pittsburgh, PA, USA.
Heather L JonesUniversity of Pittsburgh Medical Center, Pittsburgh, PA, USA.
James F PingpankUniversity of Pittsburgh Medical Center, Pittsburgh, PA, USA.
Zachary C LiptonCarnegie Mellon University, Pittsburgh, PA, USA.
David L BartlettAllegheny Health Network, Pittsburgh, PA, USA.
Haroon M ChoudryUniversity of Pittsburgh Medical Center, Pittsburgh, PA, USA.
University of Pittsburgh Medical Center · USCarnegie Mellon University · USUniversity of California, San Francisco · USAllegheny Health Network · USColumbia University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCRS-HIPEC provides oncologic benefit in well-selected patients with peritoneal carcinomatosis; however, it is a morbid procedure. Decision tools for preoperative patient selection are limited. We developed a risk score to predict severity of 90 day complications for cytoreductive surgery with hyperthermic intraperitoneal chemotherapy (CRS-HIPEC). PATIENTS AND

methodsAdults who underwent CRS-HIPEC at the University of Pittsburgh Medical Center (March 2001-April 2020) were analyzed as part of this study. Primary endpoint was severe complications within 90 days following CRS-HIPEC, defined using Comprehensive Complication Index (CCI) scores as a dichotomous (determined using restricted cubic splines) and continuous variable. Data were divided into training and test sets. Several machine learning and traditional algorithms were considered.

resultsFor the 1959 CRS-HIPEC procedures included, CCI ranged from 0 to 100 (median 32.0). Adjusted restricted cubic splines model defined severe complications as CCI > 61. A minimum of 20 variables achieved optimal performance of any of the models. Linear regression achieved the highest area under the receiving operator characteristic curve (AUC, 0.74) and outperformed the NSQIP Surgical Risk calculator (AUC 0.80 vs. 0.66). Factors most positively associated with severe complications included peritoneal carcinomatosis index score, symptomatic status, and undergoing pancreatectomy, while American Society of Anesthesiologists 2 class, appendiceal diagnosis, and preoperative albumin were most negatively associated with severe complications.

conclusionsThis study refines our ability to predict severe complications within 90 days of discharge from a hospitalization in which CRS-HIPEC was performed. This advancement is timely and relevant given the growing interest in this procedure and may have implications for patient selection, patient and referring provider comfort, and survival.

Indexed as

Hyperthermia, InducedPeritoneal NeoplasmsAdultAntineoplastic Combined Chemotherapy ProtocolsChemotherapy, AdjuvantCombined Modality TherapyCytoreduction Surgical ProceduresHumansJudgmentRetrospective StudiesSurvival Rate

Identifiers

PMID37266808
OpenAlexW4379095122

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.