Dataset Information

Variation in breast cancer grading in 1,636 resections assessed using control charts and in silico kappa.

ABSTRACT:

Objective

Assess interpretative variation in Nottingham grading using control charts (CCs) and in silico kappa (ISK).

Methods

In house invasive breast cancer cases (2011-2019) at two institutions with a synoptic report were extracted. Pathologist interpretative rates (PIRs) were calculated and normed for Nottingham grade (G) and its components (tubular score (TS), nuclear score (NS), mitotic score (MS)) for pathologists interpreting >35 cases. ISKs were calculated using the ordered mutually exclusive category assumption (OMECA) and maximal categorical overlap assumption (MCOA).

Results

The study period included 1,994 resections. Ten pathologists each assessed 38-441 cases and together saw 1,636; these were further analyzed. The PIR medians (normed ranges) were: G1:24%(18-27%), G2:53%(43-56%) and G3:26%(19-33%). The MCOA ISK and the number of statistical outliers (p< 0.05/p< 0.001) to the group median interpretive rate (GMIR) for the ten pathologists was G1: 0.82(2/0 of 10), G2: 0.76(1/1), G3: 0.71(3/1), TS1: 0.79(1/0), TS2: 0.63(5/1), TS3: 0.66(5/1), NS1: 0.37(5/4), NS2: 0.60(4/3), NS3: 0.59(4/4), MS1: 0.78(3/1), MS2: 0.78(3/1), MS3: 0.77(2/0). The OMECA ISK was 0.62, 0.49, 0.69 and 0.71 for TS, NS, MS and G.

Conclusions

The nuclear score has the most outliers. NS1 appears to be inconsistently used. ISK mirrors trends in conventional kappa studies. CCs and ISK allow insight into interpretive variation and may be essential for the next generation in quality.

SUBMITTER: Moodley J

PROVIDER: S-EPMC7769472 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Variation in breast cancer grading in 1,636 resections assessed using control charts and in silico kappa.

Moodley Jinesa J Williams Phillip P Gohla Gabriela G Major Pierre P Bonert Michael M

PloS one 20201228 12

<h4>Objective</h4>Assess interpretative variation in Nottingham grading using control charts (CCs) and in silico kappa (ISK).<h4>Methods</h4>In house invasive breast cancer cases (2011-2019) at two institutions with a synoptic report were extracted. Pathologist interpretative rates (PIRs) were calculated and normed for Nottingham grade (G) and its components (tubular score (TS), nuclear score (NS), mitotic score (MS)) for pathologists interpreting >35 cases. ISKs were calculated using the ordere ...[more]

PMID: 33370310

Similar Datasets

Project description:ObjectivesTo determine whether an innovative graphical tool for accurate measurement of individual surgeon performance metrics, adjusted for both surgeon-specific and patient-specific factors, significantly alters interpretation of performance data.DesignRetrospective analysis of all total knee replacements (TKRs) conducted at the host institution between 1996 and 2009. The database was randomly divided into training and testing datasets. Using multivariate generalised estimating equation regression models, the training dataset enabled generation of patient-risk and surgeon-experience adjustment factors. To simulate prospective monitoring of individual surgeon outcomes, the testing dataset was mapped on control charts. Weighted ? statistics were calculated to measure the agreement between patient-risk adjusted and fully adjusted control charts.SettingTertiary care academic hospital.ParticipantsAll patients undergoing TKR at the host institution 1996-2009.Main outcome measureOperative efficiency.Results5313 procedures were analysed. Adjusted control charts were generated using a training dataset comprising 3756 procedures performed by 13 surgeons. The operative time gradually declined by 121 min with 25 years of experience (p<0.0001). Charts were tested by monitoring four other surgeons, performing an average of 389 procedures each. Adjustment for surgeon experience significantly altered the interpretation of operative efficiency (?=0.29 (95% CI 0.11 to 0.47)), and enhanced assessment of a surgeon's improvement or diminishment in efficiency over time. Specifically, experience adjustment inverted the interpretation of surgeon efficiency from above average to below average, or from improving to declining performance.ConclusionsAdjustment for surgeon experience is necessary for accurate interpretation of metrics over the course of a surgeon's career. Patient-adjusted and surgeon-adjusted control charts provide an accurate method of monitoring individual operative efficiency.

Project description:ObjectiveTo determine the effect of introducing prospective monitoring of outcomes using control charts and regular feedback on indicators to surgical teams on major adverse events in patients.DesignNational, parallel, cluster randomised trial embedding a difference-in-differences analysis.Setting40 surgical departments of hospitals across France.Participants155 362 adults who underwent digestive tract surgery. 20 of the surgical departments were randomised to prospective monitoring of outcomes using control charts with regular feedback on indicators (intervention group) and 20 to usual care only (control group).InterventionsProspective monitoring of outcomes using control charts, provided in sets quarterly, with regular feedback on indicators (intervention hospitals). To facilitate implementation of the programme, study champion partnerships were established at each site, comprising a surgeon and another member of the surgical team (surgeon, anaesthetist, or nurse), and were trained to conduct team meetings, display posters in operating rooms, maintain a logbook, and devise an improvement plan.Main outcome measuresThe primary outcome was a composite of major adverse events (inpatient death, intensive care stay, reoperation, and severe complications) within 30 days after surgery. Changes in surgical outcomes were compared before and after implementation of the programme between intervention and control hospitals, with adjustment for patient mix and clustering.Results75 047 patients were analysed in the intervention hospitals (37 579 before and 37 468 after programme implementation) versus 80 315 in the control hospitals (41 548 and 38 767). After introduction of the control chart, the absolute risk of a major adverse event was reduced by 0.9% (95% confidence interval 0.4% to 1.4%) in intervention compared with control hospitals, corresponding to 114 patients (70 to 280) who needed to receive the intervention to prevent one major adverse event. A significant decrease in major adverse events (adjusted ratio of odds ratios 0.89, 95% confidence interval 0.83 to 0.96), patient death (0.84, 0.71 to 0.99), and intensive care stay (0.85, 0.76 to 0.94) was found in intervention compared with control hospitals. The same trend was observed for reoperation (0.91, 0.82 to 1.00), whereas severe complications remained unchanged (0.96, 0.87 to 1.07). Among the intervention hospitals, the effect size was proportional to the degree of control chart implementation witnessed. Highly compliant hospitals experienced a more important reduction in major adverse events (0.84, 0.77 to 0.92), patient death (0.78, 0.63 to 0.97), intensive care stay (0.76, 0.67 to 0.87), and reoperation (0.84, 0.74 to 0.96).ConclusionsThe implementation of control charts with feedback on indicators to surgical teams was associated with concomitant reductions in major adverse events in patients. Understanding variations in surgical outcomes and how to provide safe surgery is imperative for improvements.Trial registrationClinicalTrials.gov NCT02569450.

Dataset Information

Variation in breast cancer grading in 1,636 resections assessed using control charts and in silico kappa.

Objective

Methods

Results

Conclusions

Publications

Variation in breast cancer grading in 1,636 resections assessed using control charts and in silico kappa.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets