We read with interest the report on colon capsule endoscopy (CCE) in clinical practice:
lessons from a national 5-year observational prospective cohort, by Benech et al.
on behalf of the ONECC Study Group [1]. Real-life practice reports with long-term prospective follow-up, out of the scope
of clinical trials, help establish a multifaceted evidence base and improve confidence
in new approaches and modalities. Pending interim results of a big population-based
Danish trial on CCE in colorectal cancer (CRC) screening [2], this study lays out some of the main reasons that prevent CCE from being the primary
diagnostic test for the large bowel in cancer screening [3]. Interestingly, in a small, real-life, single-center cohort, using the same laxative-booster
combination, we showed that even in younger patients (median age 56 years), CCE could
achieve complete colonic examination in only 75 % of cases [4].
In a recent meta-analysis, we demonstrated that low completeness and adequate cleanliness
rates (ACRs) torment CCE irrespective of the clinical setting (observational vs randomized
clinical trials) [5]. In the same meta-analysis, we established that although polyethylene glycol (PEG)
laxative and sodium phosphate (NaP) booster were the most used, they were not associated
with higher completion rates or ACRs. In a recent systematic review [6], the use of CCE appeared to be a safe and effective tool for detecting CRC and polyps
in a CRC screening setting. Accuracy was comparable to colonoscopy and superior to
computed colonography (CTC), making CCE a good alternative to colonoscopy in CRC screening
programs, although completion rates require improvement. It is important to note that
no significant complication related to CCE was reported in this paper, despite a selected
population with many significant comorbidities.
Benech et al. providee a practical patient management algorithm, according to colon
capsule endoscopy (CCE) results obtained from the ONECC cohort. This is on par with
other published proposals [7] and the realistic medicine guidance suggested by the ScotCap clinical leads collaboration
[8]. CCE studies are time-consuming to read and interpret, and human errors are bound
to happen [9]
[10]. The application so artificial intelligence (AI) to CCE with deep learning convolutional
neural network algorithms [11] could lead to automated polyp identification and/or characterisztion with improved
sensitivity and reduced time demands by highlighting images with abnormalities for
physician review. However, AI will only detect lesions that are already visible; therefore,
future research should focus on improving bowel preparation to improve the cleanliness
and completeness rate for CCE to the recommended minimum level of 90 % for optical
colonoscopy [12].
Real-life practice data on colon capsule endoscopy: We need them fast! Anastasios Koulaouzidis, Thomas Bjørsum-Meyer, Ervin Toth Endoscopy International
Open 2022; 10: E230–E231. DOI: 10.1055/a-1728-9371
In the above-mentioned article the authorsʼ names and affiliations were corrected.
They are as follows:
Anastasios Koulaouzidis1, 2, 3, Thomas Bjørsum-Meyer4, Ervin Toth5
1 Department of Medicine, OUH Svendborg, Sygehus, Denmark
2 Department of Clinical Research, University, of Southern Denmark (SDU), Denmark
3 Department of Social Medicine & Public Health, Pomeranian Medical University, Poland
4 Surgical Research Unit, Odense University Hospital, Svendborg, Denmark
5 Department of Gastroenterology, Skåne University Hospital, Malmö, Lund University,
Sweden
This was corrected in the online version on 4 April 2022.
