Mangas-Sanjuan CADe (advanced neoplasia)

Role of Artificial Intelligence in Colonoscopy Detection of Advanced Neoplasias

Patient / Population Intervention / Exposition Comparaison Critère de jugement

In 3,213 FIT-positive adults in a Spanish colorectal cancer screening programme, computer-aided polyp detection during colonoscopy did not improve detection of advanced colorectal neoplasia compared with standard colonoscopy.

N
3 213
Schéma
Multicentre RCT, Spain
Critère
Advanced colorectal neoplasia detection rate
Pertinence
1
RésultatAdvanced neoplasia detection 34.8% vs 34.6% (aRR 1.01, 95% CI 0.92–1.10); advanced neoplasias per colonoscopy 0.54 vs 0.52 (adjusted rate ratio 1.04, 99.9% CI 0.88–1.22); ADR 64.2% vs 62.0% (aRR 1.06, 99.9% CI 0.91–1.23). CADe did increase nonpolypoid lesions (0.56 vs 0.47) and proximal adenomas (0.94 vs 0.81).
Mangas-Sanjuan C, et al. Ann Intern Med. 2023;176(9):1145-1152. 10.7326/M22-2619
Discussion et critique

The landmark negative of the cluster: in a FIT-positive screening population with high baseline detection, CADe found more small, flat and proximal lesions but no more advanced neoplasia — the lesions that matter for cancer prevention. The authors note that the high control-group ADR (62.0%) may limit generalisability to low-detector endoscopists; the trial was funded by Medtronic. With the deskilling signal (Budzyń) it reframes the ADR gains of Wang, Repici and COLO-DETECT as surrogate-endpoint wins of uncertain clinical value.