Evidence map›Paper›PMID 39212612›Full record

ArticleJournal of the National Cancer Institute2025

Assessment of intermediate-term mortality following pancreatectomy for cancer.

Lauren M Janczewski, Michael R Visenio, Rachel Hae-Soo Joung, Anthony D Yang, David D Odell, Elizabeth C Danielson, Mitchell C Posner, Ted A Skolarus, David J Bentrem, Karl Y Bilimoria and 1 more

Abstract read
In one paragraph

Article in Journal of the National Cancer Institute, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Lauren M JanczewskiDepartment of Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.ORCID 0000-0003-2721-3519
Michael R VisenioDepartment of Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.ORCID 0000-0002-3766-9942
Rachel Hae-Soo JoungDepartment of Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.ORCID 0000-0002-4120-1058
Anthony D YangDivision of Surgical Oncology, Department of Surgery, Indiana University School of Medicine, Indianapolis, IN, USA.
David D OdellDivision of Thoracic Surgery, Department of Surgery, University of Michigan School of Medicine, Ann Arbor, MI, USA.
Elizabeth C DanielsonDepartment of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.ORCID 0000-0003-2792-7140
Mitchell C PosnerDivision of Surgical Oncology, Department of Surgery, University of Chicago Pritzker School of Medicine, Chicago, IL, USA.
Ted A SkolarusDepartment of Surgery, Urology Section, University of Chicago Pritzker School of Medicine, Chicago, IL, USA.ORCID 0000-0002-5859-8151
David J BentremDepartment of Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Karl Y BilimoriaDivision of Surgical Oncology, Department of Surgery, Indiana University School of Medicine, Indianapolis, IN, USA.
Ryan P MerkowDivision of Surgical Oncology, Department of Surgery, University of Chicago Pritzker School of Medicine, Chicago, IL, USA.

Funding

COllaborative Northwestern Surgical Oncology Research Training (CONSORT)T32CA247801 · NCI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI ACKERMANN, RONALD T., KHAN, SEEMA AHSAN · 2020 to 2024
$1.3M
NCI NIH HHS T32 CA247801NCI NIH HHS T32CA247801
6 · The paper itself

Abstract

backgroundPancreatic cancer remains highly lethal, and resection represents the only chance for cure. Although patients are counseled regarding short-term (0-3 months) mortality, little is known about mortality 3-6 months (intermediate-term) following surgery. We assessed predictors of intermediate-term mortality, evaluated hospital-level variation, and developed a nomogram to predict intermediate-term mortality risk.

methodsPatients undergoing pancreatic cancer resection were identified from the National Cancer Database (2010-2020). Multivariable logistic regression identified predictors of intermediate-term mortality and assessed differences between short-term and intermediate-term mortality. Multinomial regression grouped by intermediate-term mortality quartiles evaluated hospital-level variation. A neural network model was constructed to predict intermediate-term mortality risk. All statistical tests were 2-sided.

resultsOf 45 297 patients, 3974 (8.9%) died within 6 months of surgery of which 2216 (5.1%) were intermediate-term. Intermediate-term mortality was associated with increasing T category, positive nodes, lack of systemic therapy, and positive margins (all P < .05) compared with survival beyond 6 months. Compared with short-term mortality, intermediate-term mortality was associated with treatment at high-volume hospitals, positive nodes, neoadjuvant systemic therapy, adjuvant radiotherapy, and positive margins (all P < .05). Median intermediate-term mortality rate per hospital was 4.5% (interquartile range [IQR] = 2.6-6.5). Highest quartile hospitals had decreased odds of treatment with neoadjuvant systemic therapy, neoadjuvant radiotherapy, and adjuvant radiotherapy (all P < .05). The neural network nomogram was highly accurate (accuracy = 0.9499; area under the receiver operating characteristics curve = 0.7531) in predicting individualized intermediate-term mortality risk.

conclusionNearly 10% of patients undergoing pancreatectomy for cancer died within 6 months, of which one-half occurred in the intermediate term. These data have real-world implications to improve shared decision making when discussing curative-intent pancreatectomy.

Indexed as

NomogramsPancreatectomyPancreatic NeoplasmsAgedFemaleHumansMaleMiddle AgedRisk FactorsSurvival RateUnited States

Identifiers

PMID39212612
PMCPMC11717425

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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.