Evidence map›Paper›PMID 39913511›Full record

ReviewThe Indian journal of medical research2024

Lung cancer screening in India: Preparing for the future using smart tools & biomarkers to identify highest risk individuals.

Nithya Ramnath, Prasanth Ganesan, Prasanth Penumadu, Douglas Arenberg, Alex Bryant

Abstract readReview
In one paragraph

Review in The Indian journal of medical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Nithya RamnathDepartment of Internal Medicine, University of Michigan, United States.
Prasanth GanesanDepartment of Medical Oncology, Jawaharlal Institute of Post Graduate Medical Education and Research, Puducherry, India.
Prasanth PenumaduDepartment of Surgical Oncology, Sri Venkateswara Institute of Cancer Care & Advanced Research, Tirupati, India.
Douglas ArenbergDepartment of Internal Medicine, University of Michigan, United States.
Alex BryantDepartment of Internal Medicine, University of Michigan, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is a growing burden of lung cancer cases in India, incidence projected to increase from 63,708 cases (2015) to 81,219 cases (2025). The increasing numbers are attributed to smoking (India currently has nearly 100 million adult smokers) and environmental pollution. Most patients present with advanced disease (80-85% are incurable), causing nearly 60,000 annual deaths from lung cancer. Early detection through lung cancer screening (LCS) can result in curative therapies for earlier stages of lung cancer and improved survival. Annual low-dose computerized tomography (LDCT) is the standard method for LCS. Usually, high-risk populations (age>50 yr and >20 pack-years of smoking) are considered for LCS, but even such focused screening may be challenging in resource-limited countries like India. However, developing a smart LCS programme with high yield may be possible by leveraging demographic and genomic data, use of smart tools, and judicious use of blood-based biomarkers. Developing this model over the next several years will facilitate a structured cancer screening programme for populations at the highest risk of lung cancer. In this paper, we discuss the demographics of lung cancer in India and its relation to smoking patterns. Further, we elaborate on the potential applications and challenges of bringing a smart approach to LCS in high-risk populations in India.

Indexed as

Biomarkers, TumorEarly Detection of CancerLung NeoplasmsSmokingHumansIndiaMass ScreeningRisk FactorsTomography, X-Ray ComputedBiomarkers, TumorArtificial intelligencebiomarkershigh-risk populationIndialow-dose CT scanslung cancerscreening

Identifiers

PMID39913511
PMCPMC11801781

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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.