Validation of claims-based algorithms for rheumatoid arthritis in Japan: Results from the VALIDATE-J study

AIM

Validity of Algorithms in Large Databases: Infectious Diseases, Rheumatoid Arthritis, and Tumor Evaluation in Japan (VALIDATE-J) study examined algorithms for identifying rheumatoid arthritis (RA) in Japanese claims data.

METHODS

VALIDATE-J was a multicenter, cross-sectional retrospective study. Disease-identifying algorithms were used to detect RA diagnosed between January 2012 and December 2016 using claims data from two Japanese hospitals. An RA diagnosis was confirmed using one of four gold standard definitions. Positive predictive values (PPVs) were calculated for prevalent (regardless of baseline RA-free period) and incident (preceded by a 12-month RA-free period) cases.

RESULTS

Of patients identified using claims-based algorithms, a random sample of 389 prevalent and 134 incident cases of RA were included. Cases identified by an RA diagnosis, no diagnosis of psoriasis, and treatment with any disease-modifying antirheumatic drugs (DMARDs) resulted in the highest PPVs versus other claims-based treatment categories (29.0%-88.3% [prevalent] and 41.0%-78.2% [incident]); cases identified by an RA diagnosis, no diagnosis of psoriasis, and glucocorticoid-only treatment had the lowest PPVs. Across claims-based algorithms, PPVs were highest when a physician diagnosis or decision by adjudicators (confirmed and probable cases) was used as the gold standard and were lowest when American College of Rheumatology/European Alliance of Associations for Rheumatology 2010 criteria were applied. PPVs of claims-based algorithms for RA in patients aged ≥66 years were slightly higher versus a USA Medicare population (maximum PPVs of 95.0% and 88.9%, respectively).

CONCLUSION

VALIDATE-J demonstrated high PPVs for most claims-based algorithms for diagnosis of prevalent and incident RA using Japanese claims data. These findings will help inform appropriate RA definitions for future claims database research in Japan.

Validity of claims-based diagnoses for infectious diseases common among immunocompromised patients in Japan

BACKGROUND

To validate Japanese claims-based disease-identifying algorithms for herpes zoster (HZ), Mycobacterium tuberculosis (MTB), nontuberculous mycobacteria infections (NTM), and Pneumocystis jirovecii pneumonia (PJP).

METHODS

VALIDATE-J, a multicenter, cross-sectional, retrospective study, reviewed the administrative claims data and medical records from two Japanese hospitals. Claims-based algorithms were developed by experts to identify HZ, MTB, NTM, and PJP cases among patients treated 2012-2016. Diagnosis was confirmed with three gold standard definitions; positive predictive values (PPVs) were calculated for prevalent (regardless of baseline disease-free period) and incident (preceded by a 12-month disease-free period for the target conditions) cases.

RESULTS

Of patients identified using claims-based algorithms, a random sample of 377 cases was included: HZ (n = 95 [55 incident cases]); MTB (n = 100 [58]); NTM (n = 82 [50]); and PJP (n = 100 [84]). PPVs ranged from 67.4-70.5% (HZ), 67.0-90.0% (MTB), 18.3-63.4% (NTM), and 20.0-45.0% (PJP) for prevalent cases, and 69.1-70.9% (HZ), 58.6-87.9% (MTB), 10.0-56.0% (NTM), and 22.6-51.2% (PJP) for incident cases, across definitions. Adding treatment to the algorithms increased PPVs for HZ, with a small increase observed for prevalent cases of NTM.

CONCLUSIONS

VALIDATE-J demonstrated moderate to high PPVs for disease-identifying algorithms for HZ and MTB using Japanese claims data.

Validity of claims-based algorithms for selected cancers in Japan: Results from the VALIDATE-J study

Purpose

Real‐world data from large administrative claims databases in Japan have recently become available, but limited evidence exists to support their validity. VALIDATE‐J validated claims‐based algorithms for selected cancers in Japan.

Methods

VALIDATE‐J was a multicenter, cross‐sectional, retrospective study. Disease‐identifying algorithms were used to identify cancers diagnosed between January or March 2012 and December 2016 using claims data from two hospitals in Japan. Positive predictive values (PPVs), specificity, and sensitivity were calculated for prevalent (regardless of baseline cancer‐free period) and incident (12‐month cancer‐free period; with claims and registry periods in the same month) cases, using hospital cancer registry data as gold standard.

Results

22 108 cancers were identified in the hospital claims databases. PPVs (number of registry cases) for prevalent/incident cases were: any malignancy 79.0% (25 934)/73.1% (18 119); colorectal 84.4% (3519)/65.6% (2340); gastric 87.4% (3534)/76.8% (2279); lung 88.1% (2066)/79.9% (1636); breast 86.4% (4959)/59.9% (3185); pancreatic 87.1% (582)/80.4% (508); melanoma 48.7% (46)/42.9% (36); and lymphoma 83.6% (1457)/77.8% (1035). Specificity ranged from 98.3% to 100% (prevalent)/99.5% to 100% (incident); sensitivity ranged from 39.1% to 67.6% (prevalent)/12.5% to 31.4% (incident). PPVs of claims‐based algorithms for several cancers in patients ≥66 years of age were slightly higher than those in a US Medicare population.

Conclusions

VALIDATE‐J demonstrated high specificity and modest‐to‐moderate sensitivity for claims‐based algorithms of most malignancies using Japanese claims data. Use of claims‐based algorithms will enable identification of patient populations from claims databases, while avoiding direct patient identification. Further research is needed to confirm the generalizability of our results and applicability to specific subgroups of patient populations.

Real-world safety of palbociclib in breast cancer patients in the United States: a new user cohort study

Background

There is limited real-world safety information on palbociclib for treatment of advanced stage HR+/HER2- breast cancer.

Methods

We conducted a cohort study of breast cancer patients initiating palbociclib and fulvestrant from February 2015 to September 2017 using the HealthCore Integrated Research Database (HIRD), a longitudinal claims database of commercial health plan members in the United States.

The historical comparator cohort comprised patients initiating fulvestrant monotherapy from January 2011 to January 2015. Propensity score matching and Cox regression were used to estimate hazard ratios for various safety events. For acute liver injury (ALI), additional analyses and medical record validation were conducted.

Results

There were 2445 patients who initiated palbociclib including 566 new users of palbociclib-fulvestrant, and 2316 historical new users of fulvestrant monotherapy. Compared to these historical new users of fulvestrant monotherapy, new users of palbociclib-fulvestrant had a greater than 2-fold elevated risk for neutropenia, leukopenia, thrombocytopenia, stomatitis and mucositis, and ALI. Incidence of anemia and QT prolongation were more weakly associated, and incidences of serious infections and pulmonary embolism were similar between groups after propensity score matching. After adjustment for additional ALI risk factors, the elevated risk of ALI in new users of palbociclib-fulvestrant persisted (e.g. primary ALI algorithm hazard ratio (HR) = 3.0, 95% confidence interval (CI) = 1.1–8.4).

Conclusions

This real-world study found increased risks of several adverse events identified in clinical trials, including neutropenia, leukopenia, and thrombocytopenia, but no increased risk of serious infections or pulmonary embolism when comparing new users of palbociclib-fulvestrant to fulvestrant monotherapy. We observed an increased risk of ALI, extending clinical trial findings of significant imbalances in grade 3/4 elevations of alanine aminotransferase (ALT).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-07790-z.

National impact of 13-valent pneumococcal conjugate vaccine on ambulatory care visits for otitis media in children under 5 years in the United States

OBJECTIVE

The 7- and 13-valent pneumococcal conjugate vaccines (PCV7 and PCV13) were approved in the US in 2000 and 2010, respectively, for active immunization against invasive disease caused by all vaccine serotypes and otitis media (OM) caused by 7 serotypes common to both vaccines, starting at ∼6 weeks of age. This study assessed the impact of PCV13 on OM by evaluating changes in US ambulatory care visit rates between the period before PCV7 (1997-1999), during PCV7 (2001-2009), and after the introduction of PCV13 (2011-2013) among US children <5 years old.

METHODS

This ecological study used US National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey data. Trend analyses using weighted least-squares regression and mean visit rates were calculated for OM and two control endpoints not likely to be related to either vaccine (skin rash and trauma).

RESULTS

Among children <5 and < 2 years old, the observed reduction in OM visit rates was 22% (95%CI: 12%-32%) and 24% (95%CI: 13%-35%) when comparing PCV13 to PCV7 periods, and 41% (95%CI: 30%-52%) and 48% (95%CI: 37%-59%) when comparing PCV13 to pre-PCV7 periods. Visit rates for skin rash and trauma remained stable.

CONCLUSION

Significant reductions in US ambulatory care visit rates for OM were observed among children aged <5 years after introduction of PCV13 compared to the periods before and during PCV7; reductions were greatest among children <2 years old. The reductions beyond the PCV7 period support the effectiveness of the vaccine's 6 additional serotypes in preventing OM.

Predictive model algorithms identifying early and advanced stage ER+/HER2- breast cancer in claims data

PURPOSE

Claims databases offer large populations for research, but lack clinical details. We aimed to develop predictive models to identify estrogen receptor positive (ER+) and human epidermal growth factor negative (HER2-) early breast cancer (ESBC) and advanced stage breast cancer (ASBC) in a claims database.

METHODS

Female breast cancer cases in Anthem's Cancer Care Quality Program served as the gold standard validation sample. Predictive models were developed from clinical knowledge and empirically from claims data using logistic and lasso regression. Model performance was assessed by classification rates and c-statistics. Models were applied to the HealthCore Integrated Research Database (claims) to identify cohorts of women with ER+/HER2- ESBC and ASBC.

RESULTS

The validation sample included 3184 women with ER+/HER2- ESBC and 1436 with ER+/HER2- ASBC. Predictive models for ER+/HER2- ESBC and ASBC included 25 and 20 factors, respectively. Models had robust discrimination in identifying cases (c-stat = 0.92 for ESBC and 0.95 for ASBC). Compared with a traditional a priori algorithm developed with clinical insight alone, the ER+/HER2- ASBC-predictive model had better positive predictive value (PPV) (0.91, 95% CI, 0.90-0.93, vs 0.69, 95% CI, 0.66-0.73) and sensitivity (0.54 vs 0.35). Models were applied to the claims database to identify cohorts of 33 001 and 3198 women with ER+/HER2- ESBC and ASBC.

CONCLUSION

We conducted a validation study and developed predictive models to identify in a claims database cohorts of women with ER+/HER2- ESBC and ASBC. The models identified large cohorts in the claims data that can be used to characterize indications in the evaluation of targeted therapies.

Comorbidity and mortality following hip fracture: a population-based cohort study

BACKGROUND AND AIMS

Identifying predictors for mortality following hip fracture is essential in order to improve survival, especially among the elderly. We compared mortality after hip fracture to controls without hip fracture, and assessed the impact of comorbidity on mortality following hip fracture in a population-based cohort study.

METHODS

The health care databases in Western Denmark (1.4 million inhabitants) were used to identify all persons > or = 40 years of age with first-time hospitalization for hip fracture between 1/1/1998 and 1/31/2003. Five population controls without hip fracture were matched to hip fracture patients on age and gender. Prior hospitalization for selected comorbidities among hip fracture subjects was assessed from hospital discharge registries. Cox regression analysis was used to compute crude and adjusted relative risks and 95% confidence intervals for 30-day, 90-day, and 1-year mortality associated with hip fracture, and with prior hospital history of selected comorbidities.

RESULTS

The cohort was followed for an average of 22 months. Females comprised 71% of the cohort and 90% was aged 65 years or older. Compared to persons without hip fracture, persons with hip fracture had from 2 to >3-fold higher risk of death at 1 year. History of congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD), dementia, tumor, and malignancy increased adjusted 1-year mortality from 50% to 3-fold among persons with hip fracture.

CONCLUSIONS

Hip fracture increased 1-year mortality more than 3-fold compared with mortality without hip fracture. Among hip fracture subjects, the presence of selected comorbidities further increased the risk of mortality after hip fracture.

Cardiovascular and respiratory hospitalizations and mortality among users of tiotropium in Denmark

Tiotropium (Spiriva is an inhaled, once-daily anticholinergic medication for chronic obstructive pulmonary disease (COPD). We conducted a population-based cohort study to examine the risk of cardiovascular and respiratory hospitalizations and mortality with tiotropium. Using the Danish healthcare registries, we identified persons >/=40 years old in three counties who were hospitalized for COPD from 1/1/1977 to 12/31/2003. Respiratory and cardiovascular medications were assessed from dispensing records. Cox regression was used to compute incidence rate ratios (RR) and 95% confidence intervals (CI) for hospitalization and death between 1/1/2002 and 12/31/2003, associated with periods of tiotropium use compared to non-use, controlling for age, gender, time since COPD, concomitant respiratory and cardiovascular medications, prior hospitalizations and Charlson comorbidity index. Among persons with COPD (10,603), 75% were >/=60 years old. Follow-up was >/=18 months for 64%. Among those exposed to tiotropium compared to periods of non-use, the RR for total and cause-specific hospitalization endpoints were not elevated except for COPD hospitalization (RR = 1.52, 95% CI: 1.29, 1.79). Mortality endpoints included total mortality (RR = 0.77, 95% CI: 0.65, 0.91), respiratory mortality (RR = 0.79, 95% CI: 0.60, 1.04), sudden death (RR = 0.71, 95% CI: 0.21, 2.34), cardiac arrest (RR = 0.74, 95% CI: 0.42, 1.32), heart failure (RR = 0.84, 95% CI: 0.41, 1.75), and myocardial infarction (RR = 1.25, 95% CI: 0.49, 3.17). Compared to periods of non-use, tiotropium was associated with reduced respiratory and overall mortality and was not associated with increased cardiac mortality. An increase in COPD hospitalization is inconsistent with clinical trial data and suggests preferential prescribing due to disease severity.

Chronic obstructive pulmonary disease severity and cardiovascular outcomes

OBJECTIVE

To identify predictors of chronic obstructive pulmonary disease (COPD) severity and assess the relation between COPD severity and risk of cardiovascular outcomes.

STUDY DESIGN AND SETTING

A cohort of patients with diagnosed and treated COPD was compiled from the Saskatchewan Health longitudinal databases. We used multivariate modeling to identify predictors of hospitalization for COPD as an indicator of COPD severity, and we used the model to characterize patients according to quintiles of COPD severity. These severity levels were used as independent variables in multivariate models of cardiovascular outcomes.

RESULTS

Determinants of COPD severity included emphysema, recent nebulizer use, home oxygen services, corticosteroid use, frequent bronchodilator use, pneumonia and prior COPD exacerbation. The 20% of patients with the highest COPD severity were 1.27 (CI: 1.07-1.50) times more likely to have arrhythmia, 1.25 (CI: 1.07-1.46) times more likely to have ischemic heart disease, 1.38 (CI: 1.11-1.71) times more likely to have angina, 2.28 (CI: 1.95-2.66) times more likely to have congestive heart failure, and 1.63 (CI: 1.22-2.16) times more likely to die of cardiovascular causes than the least severe 20% of patients.

CONCLUSIONS

Patients with more severe COPD, as defined by our model, had higher cardiovascular morbidity and mortality than patients with less severe COPD.

Bias due to False-Positive Diagnoses in an Automated Health Insurance Claims Database

BACKGROUND AND OBJECTIVE

Automated database studies have become a cornerstone of drug safety assessment. To assess the reliability of automated data, we compared the hospitalisation and mortality rates among three similar studies of automated healthcare databases in North America.

METHODS

Similar protocols were used to identify patients diagnosed with chronic obstructive pulmonary disease (COPD) who were treated with inhaled bronchodilators or inhaled corticosteroids in the Saskatchewan Health Database (SHD), the Kaiser Permanente Medical Care Program (KPMCP) of Northern California, and a proprietary automated insurance claims database available from i3 (formerly Ingenix). Automated data were used to compute incidence rates of total hospitalisation, cardiovascular (CV) hospitalisation and hospitalisation due to several specific types of CV outcomes. Record linkage with registries of vital statistics was used to identify deaths, obtain death certificates, and compute rates of total mortality, CV mortality and deaths due to certain CV outcomes. We compared rates in the i3 population with rates in the other two populations using age-adjusted rate ratio estimates and 95% CIs.

RESULTS

The i3 cohort had approximately one-half the rates of total mortality, CV mortality and total hospitalisations, but twice the rate of CV hospitalisations, compared with each of the other two database cohorts.

DISCUSSION

The unexpectedly higher rates of CV hospitalisations in the i3 population are inconsistent with its lower CV mortality, total mortality and total hospitalisation rates. This discrepancy is not readily explained by a higher prevalence of CV disease or procedures, random variation or confounding. Instead, high CV hospitalisation rates in the i3 population are consistent with a high rate of false-positive diagnoses recorded on insurance billing claims.

CONCLUSION

These results underscore the importance of ensuring valid endpoints in automated claims databases.