Overall Polyp Detection Rate as a Surrogate Measure for Screening Efficacy Independent of Histopathology: Evidence from National Endoscopy Database
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SUBMITTER: Aloysius M
PROVIDER: S-EPMC11204558 | biostudies-literature | 2024 May
REPOSITORIES: biostudies-literature
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Project description:Background To address mismatch between routine endoscopy capacity and demand, centers often implement initiatives to increase capacity, such as weekend working or using locums/agency staff (insourcing). However, there are concerns that such initiatives may negatively impact quality. We investigated polyp detection for weekend vs. weekday and insourced vs. standard procedures using data from the UK National Endoscopy Database.Methods We conducted a national, retrospective, cross-sectional study of diagnostic colonoscopies performed during 01/01-04/04/2019. The primary outcome was mean number of polyps (MNP) and the secondary outcome was polyp detection rate (PDR). Multi-level mixed-effect regression, fitting endoscopist as a random effect, was used to examine associations between procedure day (weekend/weekday) and type (insourced/standard) and these outcomes, adjusting for patient age, sex, and indication.Results 92 879 colonoscopies (weekends: 19 977 [21.5 %]; insourced: 9909 [10.7 %]) were performed by 2496 endoscopists. For weekend colonoscopies, patients were less often male or undergoing screening-related procedures; for insourced colonoscopies, patients were younger and less often undergoing screening-related procedures (all P < 0.05). Fully adjusted MNP was significantly lower for weekend vs. weekday (incidence rate ratio [IRR] 0.86 [95 %CI 0.83-0.89]) and for insourced vs. standard procedures (IRR 0.91 [95 %CI 0.87-0.95]). MNP was highest for weekday standard procedures and lowest for weekend insourced procedures; there was no interaction between procedure day and type. Similar associations were found for PDR.Conclusions Strategies to increase colonoscopy capacity may negatively impact polyp detection and should be monitored for quality. Reasons for this unwarranted variation require investigation.
| S-EPMC10978102 | biostudies-literature
Project description:IntroductionQuality measures for colonoscopy such as adenoma detection rate (ADR) have been proposed to be surveilled for ensuring minimum standards. However, its direct measurement is time consuming and often neglected. Extrapolating ADR and other quality measures from polyp detection rate (PDR) can be a pragmatic alternative.ObjectiveTo determine quotients for estimating ADR and sessile serrated adenoma/polyp detection rate (SSA/P-DR) from PDR in an Australian cohort.MethodsConsecutive adult patient colonoscopies during a 1-year period were retrospectively assessed in a single Australian tertiary endoscopy center. Adenoma detection quotient (ADQ) and SSA/P detection quotient (SSA/P-DQ) were defined as the division of ADR and SSA/P-DR by PDR, respectively. The primary outcome was the number of procedures to achieve a stable cumulative ADQ and SSA/P-DQ. Secondary outcomes included evaluation of ADQ and SSA/P-DQ in different subsets.ResultsIn total, 2,657 colonoscopies were performed by 15 endoscopists in 2016. The ADR, SSA/P-DR, and PDR found were 32.2, 6.7, and 47.3%, respectively. The ADQ and SSA/P-DQ values found were 0.68 and 0.14, respectively. After approximately 500 procedures, both ADQ and SSA/P-DQ became stable. Interclass correlation coefficient (ICC) for the prediction of ADR from ADQ was excellent for all endoscopists that performed >177 procedures in that year (ICC 0.84).ConclusionsADQ and SSA/P-DQ values were consistent when over 500 procedures were analyzed. ADQ had an excellent correlation with ADR when >177 procedures per endoscopist were evaluated.
| S-EPMC7445665 | biostudies-literature
Project description:BackgroundThe Trans.IT database is a national gastrointestinal (GI) endoscopy database developed in 2012. It automatically collects anonymous data from GI endoscopy procedures in a centralized database. All endoscopists use a structured reporting tool for uniform data collection. In this study, we aim to provide an overview of the database and to evaluate its impact on data registration quality.MethodsWe used all ERCPs, colonoscopies and colorectal cancer (CRC)-screening colonoscopies performed between 2016 and 2020. We excluded centers joining after 2016 and patients below age 18. Data registration quality for ERCPs included completeness of data for: intention of ERCP, Schutz score, ASA classification, papillary status (virgin or previous sphincterotomy), cannulation (success or failure to cannulate the desired duct) and procedural success. For colonoscopies: indication, ASA-classification, Boston Bowel Preparation Score (BBPS), cecal intubation, polyp detection rate (PDR). For CRC-screening colonoscopies, ASA-classification, BBPS, cecal intubation, PDR and adenoma detection rate (ADR).ResultsA total of 14,156 ERCPs, 150,962 colonoscopies and 37,199 colorectal cancer screening colonoscopies were included in our analysis. For ERCPs, registration of procedural intention, Schutz score, ASA classification, papillary status, cannulation and procedural success improved from 34.9%, 32.7%, 72.6%, 36.5%, 34.6%, 27.2% in 2016, to 86.4%, 84.6%, 97.4%, 86.4%, 82.1%, 84.0%, respectively, in 2020. For non-screening colonoscopies, registration of indication, ASA classification, BBPS, cecal intubation and PDR improved from 40.4%, 60.5%, 47.6%, 69.8% and 32.3% in 2016 to 90.3%, 88.9%, 59.8%, 79.1% and 39.1%, respectively, in 2020. For CRC-cancer screening colonoscopy registration equaled outcome, PDR and ADR changed from 74.7% to 63.6% in 2016 to 66.3% and 53.8% in 2020, respectively.ConclusionsThe quality of endoscopy data registration has consistently improved over the years by using the Trans.IT database. This is most likely the result of feedback to performing endoscopists to review performance in real-time online and progressive awareness of quality of data registration.
| S-EPMC11578836 | biostudies-literature
Project description:ObjectivesConvolutional neural networks (CNN) for computer-aided diagnosis of polyps are often trained using high-quality still images in a single chromoendoscopy imaging modality with sessile serrated lesions (SSLs) often excluded. This study developed a CNN from videos to classify polyps as adenomatous or nonadenomatous using standard narrow-band imaging (NBI) and NBI-near focus (NBI-NF) and created a publicly accessible polyp video database.MethodsWe trained a CNN with 16,832 high and moderate quality frames from 229 polyp videos (56 SSLs). It was evaluated with 222 polyp videos (36 SSLs) across two test-sets. Test-set I consists of 14,320 frames (157 polyps, 111 diminutive). Test-set II, which is publicly accessible, 3317 video frames (65 polyps, 41 diminutive), which was benchmarked with three expert and three nonexpert endoscopists.ResultsSensitivity for adenoma characterization was 91.6% in test-set I and 89.7% in test-set II. Specificity was 91.9% and 88.5%. Sensitivity for diminutive polyps was 89.9% and 87.5%; specificity 90.5% and 88.2%. In NBI-NF, sensitivity was 89.4% and 89.5%, with a specificity of 94.7% and 83.3%. In NBI, sensitivity was 85.3% and 91.7%, with a specificity of 87.5% and 90.0%, respectively. The CNN achieved preservation and incorporation of valuable endoscopic innovations (PIVI)-1 and PIVI-2 thresholds for each test-set. In the benchmarking of test-set II, the CNN was significantly more accurate than nonexperts (13.8% difference [95% confidence interval 3.2-23.6], P = 0.01) with no significant difference with experts.ConclusionsA single CNN can differentiate adenomas from SSLs and hyperplastic polyps in both NBI and NBI-NF. A publicly accessible NBI polyp video database was created and benchmarked.
| S-EPMC10570984 | biostudies-literature
Project description:A clinical validation of the bone scan lesion area (BSLA) as a quantitative imaging biomarker was performed in metastatic castration-resistant prostate cancer (mCRPC). BSLA was computed from whole-body bone scintigraphy at baseline and week 12 posttreatment in a cohort of 198 mCRPC subjects (127 treated and 71 placebo) from a clinical trial involving a different drug from the initial biomarker development. BSLA computation involved automated image normalization, lesion segmentation, and summation of the total area of segmented lesions on bone scan AP and PA views as a measure of tumor burden. As a predictive biomarker, treated subjects with baseline BSLA [Formula: see text] had longer survival than those with higher BSLA ([Formula: see text] and [Formula: see text]). As a surrogate outcome biomarker, subjects were categorized as progressive disease (PD) if the BSLA increased by a prespecified 30% or more from baseline to week 12 and non-PD otherwise. Overall survival rates between PD and non-PD groups were statistically different ([Formula: see text] and [Formula: see text]). Subjects without PD at week 12 had longer survival than subjects with PD: median 398 days versus 280 days. BSLA has now been demonstrated to be an early surrogate outcome for overall survival in different prostate cancer drug treatments.
| S-EPMC5764115 | biostudies-other
Project description:A number of studies have evaluated the psychometric properties of the Functional Independence Measure (FIM™) using Rasch analysis, although none has done so using the National Institute on Disability, Independent Living, and Rehabilitation Research Traumatic Brain Injury Model Systems National Database, a longitudinal database that captures demographic and outcome information on persons with moderate to severe traumatic brain injury across the United States. In the current study, we examine the psychometric properties of the FIM as represented by persons within this database and demonstrate that the FIM comprises three subscales representing cognitive, self-care, and mobility domains. These subscales were analyzed simultaneously using a multivariate Rasch model in combination with a time dependent concurrent calibration scheme with the goal of creating a raw score-to-logit transformation that can be used to improve the accuracy of parametric statistical analyses. The bowel and bladder function items were removed because of misfit with the motor and cognitive items. Some motor items exhibited step disorder, which was addressed by collapsing Categories 1-3 for Toileting, Stairs, Locomotion, Tub/Shower Transfers; Categories 1 and 2 for Toilet and Bed Transfers; and Categories 2 and 3 for Grooming. The strong correlations (r = 0.82-0.96) among the three subscales suggest they should be modeled together. Coefficient alpha of 0.98 indicates high internal consistency. Keyform maps are provided to enhance clinical interpretation and application of study results.
| S-EPMC6445201 | biostudies-literature
Project description:ImportanceCancer registries are important real-world data sources consisting of data abstraction from the medical record; however, patients with unknown or missing data are underrepresented in studies that use such data sources.ObjectiveTo assess the prevalence of missing data and its association with overall survival among patients with cancer.Design, setting, and participantsIn this retrospective cohort study, all variables within the National Cancer Database were reviewed for missing or unknown values for patients with the 3 most common cancers in the US who received diagnoses from January 1, 2006, to December 31, 2015. The prevalence of patient records with missing data and the association with overall survival were assessed. Data analysis was performed from February to August 2020.ExposuresAny missing data field within a patient record among 63 variables of interest from more than 130 total variables in the National Cancer Database.Main outcomes and measuresPrevalence of missing data in the medical records of patients with cancer and associated 2-year overall survival.ResultsA total of 1 198 749 patients with non-small cell lung cancer (mean [SD] age, 68.5 [10.9] years; 628 811 men [52.5%]), 2 120 775 patients with breast cancer (mean [SD] age, 61.0 [13.3] years; 2 101 758 women [99.1%]), and 1 158 635 patients with prostate cancer (mean [SD] age, 65.2 [9.0] years; 100% men) were included in the analysis. Among those with non-small cell lung cancer, 851 295 patients (71.0%) were missing data for variables of interest; 2-year overall survival was 33.2% for patients with missing data and 51.6% for patients with complete data (P < .001). Among those with breast cancer, 1 161 096 patients (54.7%) were missing data for variables of interest; 2-year overall survival was 93.2% for patients with missing data and 93.9% for patients with complete data (P < .001). Among those with prostate cancer, 460 167 patients (39.7%) were missing data for variables of interest; 2-year overall survival was 91.0% for patients with missing data and 95.6% for patients with complete data (P < .001).Conclusions and relevanceThis study found that within a large cancer registry-based real-world data source, there was a high prevalence of missing data that were unable to be ascertained from the medical record. The prevalence of missing data among patients with cancer was associated with heterogeneous differences in overall survival. Improvements in documentation and data quality are necessary to make optimal use of real-world data for clinical advancements.
| S-EPMC7988369 | biostudies-literature
Project description:BackgroundColon capsule endoscopy is a promising technique for evaluation of the colon, but its reproducibility is still unknown.ObjectiveThis study assesses intra and inter-observer agreement in evaluations of colon capsule endoscopy videos.MethodsForty-two complete colon capsule endoscopy investigations were analysed by three experts and two beginners. Intra-observer agreement was assessed in paired readings of two experts and two beginners. Agreement was determined by the intraclass correlation coefficient: poor (<0.5), moderate (0.5-0.75), good (0.75-0.9) and excellent (>0.9).ResultsAgreement on 'indication for a following colonoscopy' based on the number and size of detected polyps and bowel cleansing quality was poor among all observers. Agreement among experts on the detection of large polyps and number of polyps was moderate, but agreement on bowel cleansing quality was poor. Beginners were in moderate agreement with the experts on polyp detection. Intra-observer agreement in experts was moderate to excellent for the detection of large polyps (≥10 mm), excellent for the number of polyps, and poor to moderate for bowel cleansing quality. Intra-observer agreement in beginners was poor to moderate for all variables.ConclusionsThis study shows a poor agreement on 'indication for a following colonoscopy', but a high intra and inter-observer agreement for polyp detection among experts, as well as a moderate agreement between beginners and experts.Trial registration: NCT02303756.
| S-EPMC6297930 | biostudies-literature
Project description:Video 1A case of an inflammatory fibroid polyp of the ileum that was safely resected using gel immersion EMR with double-balloon endoscopy.
| S-EPMC10861840 | biostudies-literature
Project description:AimAs the completed studies have small sample sizes and different algorithms, a meta-analysis was conducted to assess the accuracy of WCE in identifying polyps using deep learning.MethodTwo independent reviewers searched PubMed, Embase, the Web of Science, and the Cochrane Library for potentially eligible studies published up to December 8, 2021, which were analysed on a per-image basis. STATA RevMan and Meta-DiSc were used to conduct this meta-analysis. A random effects model was used, and a subgroup and regression analysis was performed to explore sources of heterogeneity.ResultsEight studies published between 2017 and 2021 included 819 patients, and 18,414 frames were eventually included in the meta-analysis. The summary estimates for the WCE in identifying polyps by deep learning were sensitivity 0.97 (95% confidence interval (CI), 0.95-0.98); specificity 0.97 (95% CI, 0.94-0.98); positive likelihood ratio 27.19 (95% CI, 15.32-50.42); negative likelihood ratio 0.03 (95% CI 0.02-0.05); diagnostic odds ratio 873.69 (95% CI, 387.34-1970.74); and the area under the sROC curve 0.99.ConclusionWCE uses deep learning to identify polyps with high accuracy, but multicentre prospective randomized controlled studies are needed in the future.
| S-EPMC9159236 | biostudies-literature