Evidence map›Paper›PMID 38758433›Full record

Observational studyIndian journal of gastroenterology : official journal of the Indian Society of Gastroenterology2024

Application of machine-learning model to optimize colonic adenoma detection in India.

Nitin Jagtap, Rakesh Kalapala, Hardik Rughwani, Aniruddha Pratap Singh, Pradev Inavolu, Mohan Ramchandani, Sundeep Lakhtakia, P Manohar Reddy, Anuradha Sekaran, Manu Tandan and 7 more

Registry-linked trialAbstract readObservational Study
PubMed Publisher
In one paragraph

Observational study in Indian journal of gastroenterology : official journal of the Indian Society of Gastroenterology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04512729 (Detection Of Colonic Polyps In India), which is not on this 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.

NCT04512729 unknown statusnot on this map

Detection Of Colonic Polyps In India: Diagnostic Colonoscopy

Typeobservational_patient_registrySponsorAsian Institute of Gastroenterology, IndiaRan2020 to 2020Enrolled4,000ConditionsColonic Polyp, Colonic Adenoma, Colonic NeoplasmsArmsColonoscopy
3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Implementing key quality performance metrics improves colorectal adenoma detection: Evidence from India.Indian journal of gastroenterology : official journal of the Indian Society of Gastroenterology · 2026
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors.

Nitin JagtapDepartment of Medical Gastroenterology, Asian Institute of Gastroenterology, Hyderabad, 500 082, India. docnits13@gmail.com.ORCID 0000-0002-3469-0164
Rakesh KalapalaDepartment of Medical Gastroenterology, Asian Institute of Gastroenterology, Hyderabad, 500 082, India.
Hardik RughwaniDepartment of Medical Gastroenterology, Asian Institute of Gastroenterology, Hyderabad, 500 082, India.
Aniruddha Pratap SinghDepartment of Medical Gastroenterology, Asian Institute of Gastroenterology, Hyderabad, 500 082, India.
Pradev InavoluDepartment of Medical Gastroenterology, Asian Institute of Gastroenterology, Hyderabad, 500 082, India.
Mohan RamchandaniDepartment of Medical Gastroenterology, Asian Institute of Gastroenterology, Hyderabad, 500 082, India.
Sundeep LakhtakiaDepartment of Medical Gastroenterology, Asian Institute of Gastroenterology, Hyderabad, 500 082, India.
P Manohar ReddyDepartment of Medical Gastroenterology, Asian Institute of Gastroenterology, Hyderabad, 500 082, India.
Anuradha SekaranDepartment of Pathology, Asian Institute of Gastroenterology, Hyderabad, 500 082, India.
Manu TandanDepartment of Medical Gastroenterology, Asian Institute of Gastroenterology, Hyderabad, 500 082, India.
Zaheer NabiDepartment of Medical Gastroenterology, Asian Institute of Gastroenterology, Hyderabad, 500 082, India.
Jahangeer BashaDepartment of Medical Gastroenterology, Asian Institute of Gastroenterology, Hyderabad, 500 082, India.
Rajesh GuptaDepartment of Medical Gastroenterology, Asian Institute of Gastroenterology, Hyderabad, 500 082, India.
Sana Fathima MemonDepartment of Medical Gastroenterology, Asian Institute of Gastroenterology, Hyderabad, 500 082, India.
G Venkat RaoDepartment of Surgical Gastroenterology, Asian Institute of Gastroenterology, Hyderabad 500 082, India.
Prateek SharmaThe University of Kansas Medical Center, Kansas City, KS, USA.
D Nageshwar ReddyDepartment of Medical Gastroenterology, Asian Institute of Gastroenterology, Hyderabad, 500 082, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsThere is limited data on the prevalence and risk factors of colonic adenoma from the Indian sub-continent. We aimed at developing a machine-learning model to optimize colonic adenoma detection in a prospective cohort.

methodsAll consecutive adult patients undergoing diagnostic colonoscopy were enrolled between October 2020 and November 2022. Patients with a high risk of colonic adenoma were excluded. The predictive model was developed using the gradient-boosting machine (GBM)-learning method. The GBM model was optimized further by adjusting the learning rate and the number of trees and 10-fold cross-validation.

resultsTotal 10,320 patients (mean age 45.18 ± 14.82 years; 69% men) were included in the study. In the overall population, 1152 (11.2%) patients had at least one adenoma. In patients with age > 50 years, hospital-based adenoma prevalence was 19.5% (808/4144). The area under the receiver operating curve (AUC) (SD) of the logistic regression model was 72.55% (4.91), while the AUCs for deep learning, decision tree, random forest and gradient-boosted tree model were 76.25% (4.22%), 65.95% (4.01%), 79.38% (4.91%) and 84.76% (2.86%), respectively. After model optimization and cross-validation, the AUC of the gradient-boosted tree model has increased to 92.2% (1.1%).

conclusionsMachine-learning models may predict colorectal adenoma more accurately than logistic regression. A machine-learning model may help optimize the use of colonoscopy to prevent colorectal cancers.

trial registrationClinicalTrials.gov (ID: NCT04512729).

Indexed as

AdenomaColonic NeoplasmsColonoscopyMachine LearningAdultFemaleHumansIndiaLogistic ModelsMaleMiddle AgedPrevalenceProspective StudiesRisk FactorsColonic adenomaColonoscopyColorectal cancerMetabolic syndrome

Identifiers

PMID38758433

What OpenQuestion holds

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Registered trials

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.