Evidence map›Paper›PMID 31125735›Full record

Trial reportJournal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer2019

Insights for Management of Ground-Glass Opacities From the National Lung Screening Trial.

Hilary A Robbins, Hormuzd A Katki, Li C Cheung, Rebecca Landy, Christine D Berg

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

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

  1. Guideline
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. [Expert Consensus for Thermal Ablation of Pulmonary Subsolid Nodules (2021 Edition)].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2021
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Subsolid pulmonary nodules: Controversy and perspective.European journal of radiology open · 2020
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Hilary A RobbinsInternational Agency for Research on Cancer, Lyon, France. Electronic address: RobbinsH@iarc.fr.
Hormuzd A KatkiDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland.
Li C CheungDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland.
Rebecca LandyDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland.
Christine D BergDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland.

Funding

Methods for Epidemiology StudiesZIACP010181 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI ALBERT, PAUL · 2009 to 2025
$34.8M
Translating Molecular and Clinical Data to Population Lung Cancer Risk AssessmentU19CA203654 · NCI · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI Christopher I. Amos, Rayjean J. Hung · 2017 to 2026
$23.7M
Optimizing Screening for HPV-related Cancers among People Living with HIVF31CA210660 · NCI · JOHNS HOPKINS UNIVERSITY · PI ROBBINS, HILARY A. · 2016 to 2017
$82k
Intramural NIH HHS Z99 CA999999NCI NIH HHS F31 CA210660NCI NIH HHS U19 CA203654World Health Organization 001
6 · The paper itself

Abstract

backgroundIn the National Lung Screening Trial (NLST), screen-detected cancers that would not have been identified by the Lung Computed Tomographic Screening Reporting and Data System (Lung-RADS) nodule management guidelines were frequently ground-glass opacities (GGOs). Lung-RADS suggests that GGOs with diameter less than 20 mm return for annual screening, and GGOs greater than or equal to 20 mm receive 6-month follow-up. We examined whether this 20-mm threshold gives consistent management of GGOs compared with solid nodules.

methodsFirst, we calculated diameter-specific malignancy probabilities for GGOs and solid nodules in the NLST. Using the solid-nodule malignancy risks as benchmarks, we suggested risk-based management categories for GGOs based on their probability of malignancy. Second, we compared lung-cancer mortality between GGOs and solid nodules in the same risk-based category.

resultsUsing the Lung-RADS v1.0 classifications, malignancy probability is higher for GGOs than solid nodules within the same category. A risk-based classification of GGOs would assign annual screening for GGOs 4 to 5 mm (0.4% malignancy risk); 6-month follow-up for GGOs 6 to 7 mm (1.1%), 8 to 14 mm (3.0%), and 15 to 19 mm (5.2%); and 3-month follow-up for greater than or equal to 20 mm (10.9%). This reclassification would have assigned similarly fatal cancers to 3-month follow-up (hazard ratio = 2.0 for lung-cancer death in GGOs versus solid-nodule cancers, 95% confidence interval: 0.4-8.7), but for 6-month follow-up, mortality was lower in GGO cancers (hazard ratio = 0.18, 95% confidence interval: 0.05-0.67).

conclusionsIf Lung-RADS categories for GGOs were based on malignancy probability, then 6- to 19-mm GGOs would receive 6-month follow-up and greater than or equal to 20-mm GGOs would receive 3-month follow-up. Such risk-based management for GGOs could improve the sensitivity of Lung-RADS, especially for large GGO cancers. However, small GGO cancers were less aggressive than their solid-nodule counterparts.

Indexed as

Early Detection of CancerFemaleHumansLung NeoplasmsMaleTomography, X-Ray ComputedComputed tomographic screeningGround-glass opacitiesLung cancer screeningLung Computed Tomographic Screening Reporting and Data SystemMalignancy probabilityNodule classificationRisk-based screening

Identifiers

PMID31125735
PMCPMC6909540

What OpenQuestion holds

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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.