Evidence map›Paper›PMID 28274562›Full record

ArticleThe Journal of thoracic and cardiovascular surgery2017

Biopsy first: Lessons learned from Cancer and Leukemia Group B (CALGB) 140503.

Leslie J Kohman, Lin Gu, Nasser Altorki, Ernest Scalzetti, Linda J Veit, Jason M Wallen, Xiaofei Wang

Open access · bronzeAbstract readComparative StudyEquivalence TrialMulticenter Study
In one paragraph

Article in The Journal of thoracic and cardiovascular surgery, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
8.8field-weighted citation impact, top 2% 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

31 citing papers in PubMed, 1 synthesis or guideline pooled it, 73 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Leslie J KohmanDepartment of Surgery, State University of New York Upstate Medical University, Syracuse, NY. Electronic address: kohmanl@upstate.edu.
Lin GuAlliance Statistics and Data Center, Duke University Medical Center, Durham, NC.
Nasser AltorkiDepartment of Surgery, Weill Cornell Medicine, New York Presbyterian Hospital, New York, NY.
Ernest ScalzettiDepartment of Radiology, State University of New York Upstate Medical University, Syracuse, NY.
Linda J VeitDepartment of Surgery, State University of New York Upstate Medical University, Syracuse, NY.
Jason M WallenDepartment of Surgery, State University of New York Upstate Medical University, Syracuse, NY.
Xiaofei WangAlliance Statistics and Data Center, Duke University Medical Center, Durham, NC.
SUNY Upstate Medical University · USDuke Medical Center · USNewYork–Presbyterian Hospital · US

Funding

Member Site CoreU10CA180821 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI Evanthia Galanis · 2014 to 2026
$177.3M
CANCER AND LEUKEMIA GROUP B MINORITY SATELLITE SUPPLEMENU10CA031946 · NCI · UNIVERSITY OF CHICAGO · PI BERTAGNOLLI, MONICA M · 1985 to 2013
$158.4M
Statistics CoreU10CA180882 · NCI · MAYO CLINIC ROCHESTER · PI Sumithra Jay Mandrekar · 2014 to 2026
$115.0M
CANCER &LEUKEMIA GROUP B STATISTICAL CENTERU10CA033601 · NCI · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI SARGENT, DANIEL J. · 1985 to 2013
$69.4M
PARTICIPATION IN CANCER AND LEUKEMIA GROUP BU10CA021060 · NCI · UPSTATE MEDICAL UNIVERSITY · PI GRAZIANO, STEPHEN L · 1985 to 2002
$410k
CANCER AND LEUKEMIA GROUP BU10CA007968 · NCI · WEILL MEDICAL COLLEGE OF CORNELL UNIV · PI SILVER, RICHARD T · 1985 to 1992
–
NCI NIH HHS U10 CA007968NCI NIH HHS U10 CA021060NCI NIH HHS U10 CA031946NCI NIH HHS U10 CA033601NCI NIH HHS U10 CA180821NCI NIH HHS U10 CA180882
6 · The paper itself

Abstract

objectiveCancer and Leukemia Group B 140503 is an ongoing, multicenter randomized trial assessing whether sublobar resection is equivalent to lobectomy for the treatment of stage I A non-small cell lung cancer (NSCLC) ≤2 cm in diameter. The objective of this report is to determine the reasons precluding intraoperative randomization.

methodsFrom June 15, 2007, to March 22, 2013, 637 patients were preregistered to the trial. Three hundred eighty-nine were randomized successfully (61%), and 248 patients were not randomized (39%). We analyzed the reasons for nonrandomization among a subset of the nonrandomized patients (208) for whom additional data were available.

resultsOf these 208 patients, undiagnosed benign nodules (n =104, 16% of all registered patients) and understaging of NSCLC (n =45, 7% of all registered patients) were the dominant reasons precluding randomization. Granulomas represent one-quarter of the benign nodules. The understaged patients had unsuspected nodal metastases (n =28) or other more advanced NSCLC. The rate of randomization was significantly greater in those patients who had a preoperative biopsy (P <.001).

conclusionsIn a carefully monitored cohort of patients with suspected small NSCLC ≤2 cm, a substantial number are misdiagnosed (benign nodules) or understaged. These patients may not have benefited from a thoracic surgical procedure. Preoperative biopsy significantly increased the rate of correct diagnosis. Preoperative biopsy of small suspected NSCLC will reduce the number of nontherapeutic or unnecessary thoracic procedures. Accuracy in preoperative diagnosis is increasingly important as more such small nodules are discovered through lung cancer screening.

Indexed as

Patient SelectionAgedBiopsyCarcinoma, Non-Small-Cell LungDiagnostic ErrorsFemaleHumansLung NeoplasmsLymphatic MetastasisMaleMiddle AgedNeoplasm StagingPneumonectomyPredictive Value of TestsReproducibility of ResultsTreatment Outcomebiopsyclinical triallung cancerlung nodulenon–small cell lung cancersub-lobar resectionsurgeryunderstaging

Identifiers

PMID28274562
PMCPMC5441224
OpenAlexW2586387184

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.