BMC Cancer (Aug 2023)

Prevalence of subclinical lung cancer detected at autopsy: a systematic review

  • Asha Bonney,
  • Kayo Togawa,
  • Michelle Ng,
  • Michael Christie,
  • Kwun M Fong,
  • Henry Marshall,
  • Katharine See,
  • Cameron Patrick,
  • Daniel Steinfort,
  • Renee Manser

DOI
https://doi.org/10.1186/s12885-023-11224-3
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 11

Abstract

Read online

Abstract Background Lung cancer screening in high-risk populations with low-dose computed tomography is supported by international associations and recommendations. Overdiagnosis is considered a risk of screening with associated harms. The aim of this paper is to determine the prevalence of subclinical lung cancer diagnosed post-mortem to better understand the reservoir of subclinical lung cancer. Methods We searched EMBASE, PubMed, and MEDLINE databases from inception until March 2022 with no language restrictions. We considered all studies with ≥100 autopsies in adults. Two reviewers independently assessed eligibility of studies, extracted data, and assessed risk of bias of included studies. We performed a meta-analysis using a random-effects model for prevalence of subclinical lung cancer diagnosed post-mortem with sensitivity and subgroup analyses. Results A total of 13 studies with 16 730 autopsies were included. Pooled prevalence was 0.4% (95% CI 0.20 to 0.82%, I2 = 84%, tau2 = 1.19, low certainty evidence,16 730 autopsies). We performed a sensitivity analysis excluding studies which did not specify exclusion of children in their cohort, with a pooled prevalence of subclinical lung cancer of 0.87% (95% CI 0.48 to 1.57%, I2 = 71%, tau2 = 0.38, 6998 autopsies, 8 studies). Conclusions This is the first published systematic review to evaluate the prevalence of post-mortem subclinical lung cancer. Compared to autopsy systematic reviews in breast, prostate and thyroid cancers, the pooled prevalence is lower in lung cancer for subclinical cancer. This result should be interpreted with caution due to the included studies risk of bias and heterogeneity, with further high-quality studies required in target screening populations.

Keywords