Evidence map›Paper›PMID 35813719›Full record

ReviewJournal of thoracic disease2022

A guide for managing patients with stage I NSCLC: deciding between lobectomy, segmentectomy, wedge, SBRT and ablation-part 1: a guide to decision-making.

Frank C Detterbeck, Justin D Blasberg, Gavitt A Woodard, Roy H Decker, Ulas Kumbasar, Henry S Park, Vincent J Mase, Brett C Bade, Andrew X Li, Whitney S Brandt and 1 more

Abstract readReview
In one paragraph

Review in Journal of thoracic disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  8. CyberKnifeJournal of thoracic disease · 2023
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Frank C DetterbeckThoracic Surgery, Yale University School of Medicine, New Haven, CT, USA.
Justin D BlasbergThoracic Surgery, Yale University School of Medicine, New Haven, CT, USA.
Gavitt A WoodardThoracic Surgery, Yale University School of Medicine, New Haven, CT, USA.
Roy H DeckerTherapeutic Radiology, Yale University School of Medicine, New Haven, CT, USA.
Ulas KumbasarThoracic Surgery, Hacettepe University School of Medicine, Ankara, Turkey.
Henry S ParkTherapeutic Radiology, Yale University School of Medicine, New Haven, CT, USA.
Vincent J MaseThoracic Surgery, Yale University School of Medicine, New Haven, CT, USA.
Brett C BadePulmonary Medicine, Yale University School of Medicine, New Haven, CT, USA.
Andrew X LiGeneral Surgery, Yale University School of Medicine, New Haven, CT, USA.
Whitney S BrandtCardiothoracic Surgery, Washington University School of Medicine, St louis, MO, USA.
David C MadoffRadiology & Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

Background: Clinical decision-making for patients with stage I lung cancer is complex. It involves multiple options (lobectomy, segmentectomy, wedge, Stereotactic Body Radiotherapy, thermal ablation), weighing multiple outcomes (e.g., short-, intermediate-, long-term) and multiple aspects of each (e.g., magnitude of a difference, the degree of confidence in the evidence, and the applicability to the patient and setting at hand). A structure is needed to summarize the relevant evidence for an individual patient and to identify which outcomes have the greatest impact on the decision-making. Methods: Based on a systematic review from 2000-2021, evidence regarding relevant outcomes was assembled, with attention to aspects of applicability, uncertainty and effect modifiers. A framework was developed to present this information a format that enhances decision-making at the point of care for individual patients. Results: While patients often cross over several boundaries, the evidence fits into categories of healthy patients, compromised patients, and favorable tumors. In healthy patients with typical (i.e., solid spiculated) lung cancers, the impact on long-term outcomes is the major driver of treatment selection. This is only slightly ameliorated in older patients. In compromised patients increasing frailty accentuates short-term differences and diminishes long-term differences especially when considering non-surgical Discussion: A framework is provided that organizes the evidence and identifies the major drivers of decision-making for an individual patient. This facilitates blending available evidence and clinical judgment in a flexible, nuanced manner that enhances individualized clinical care.

Indexed as

ablationdecision-makingLung cancerradiotherapysurgery

Identifiers

PMID35813719
PMCPMC9264102

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.