Dataset Information

Using probabilistic record linkage and propensity-score matching to identify a community-based comparison population.

ABSTRACT: In retrospective cohort studies of interventions disseminated to communities, it is challenging to find comparison groups with high-quality data for evaluation. We present one methodological approach as part of our study of birth outcomes of second-born children in a home visiting (HV) program targeting first-time mothers. We used probabilistic record linkage to link Connecticut's Nurturing Families Network (NFN) HV program and birth-certificate data for children born from 2005 to 2015. We identified two potential comparison groups: a propensity-score-matched group from the remaining birth certificate sample and eligible-but-unenrolled families. An analysis of interpregnancy interval (IPI) is presented to exemplify the approach. We identified the birth certificates of 4822 NFN families. The propensity-score-matched group had 14,219 families (3-to-1 matching) and we identified 1101 eligible-but-unenrolled families. Covariates were well balanced for the propensity-score-matched group, but poorly balanced for the eligible-but-unenrolled group. No program effect on IPI was found. By combining propensity-score matching and probabilistic record linkage, we were able to retrospectively identify relatively large comparison groups for quasi-experimental research. Using birth certificate data, we accessed outcomes for all of these individuals from a single data source. Multiple comparison groups allow us to confirm findings when each method has some limitations. Other researchers seeking community-based comparison groups could consider a similar approach.

SUBMITTER: Holland ML

PROVIDER: S-EPMC9064948 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Using probabilistic record linkage and propensity-score matching to identify a community-based comparison population.

Holland Margaret L ML Taylor Rose M RM Condon Eileen E Rinne Gabrielle R GR Bleicher Sarah S Seldin Margaret L ML Sadler Lois S LS Li Connie C

Research in nursing & health 20220406 3

In retrospective cohort studies of interventions disseminated to communities, it is challenging to find comparison groups with high-quality data for evaluation. We present one methodological approach as part of our study of birth outcomes of second-born children in a home visiting (HV) program targeting first-time mothers. We used probabilistic record linkage to link Connecticut's Nurturing Families Network (NFN) HV program and birth-certificate data for children born from 2005 to 2015. We ident ...[more]

PMID: 35388528

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Project description:BackgroundCardinality matching (CM), a novel matching technique, finds the largest matched sample meeting prespecified balance criteria thereby overcoming limitations of propensity score matching (PSM) associated with limited covariate overlap, which are especially pronounced in studies with small sample sizes. The current study proposes a framework for large-scale CM (LS-CM); and compares large-scale PSM (LS-PSM) and LS-CM in terms of post-match sample size, covariate balance and residual confounding at progressively smaller sample sizes.MethodsEvaluation of LS-PSM and LS-CM within a comparative cohort study of new users of angiotensin-converting enzyme inhibitor (ACEI) and thiazide or thiazide-like diuretic monotherapy identified from a U.S. insurance claims database. Candidate covariates included patient demographics, and all observed prior conditions, drug exposures and procedures. Propensity scores were calculated using LASSO regression, and candidate covariates with non-zero beta coefficients in the propensity model were defined as matching covariates for use in LS-CM. One-to-one matching was performed using progressively tighter parameter settings. Covariate balance was assessed using standardized mean differences. Hazard ratios for negative control outcomes perceived as unassociated with treatment (i.e., true hazard ratio of 1) were estimated using unconditional Cox models. Residual confounding was assessed using the expected systematic error of the empirical null distribution of negative control effect estimates compared to the ground truth. To simulate diverse research conditions, analyses were repeated within 10 %, 1 and 0.5 % subsample groups with increasingly limited covariate overlap.ResultsA total of 172,117 patients (ACEI: 129,078; thiazide: 43,039) met the study criteria. As compared to LS-PSM, LS-CM was associated with increased sample retention. Although LS-PSM achieved balance across all matching covariates within the full study population, substantial matching covariate imbalance was observed within the 1 and 0.5 % subsample groups. Meanwhile, LS-CM achieved matching covariate balance across all analyses. LS-PSM was associated with better candidate covariate balance within the full study population. Otherwise, both matching techniques achieved comparable candidate covariate balance and expected systematic error.ConclusionsLS-CM found the largest matched sample meeting prespecified balance criteria while achieving comparable candidate covariate balance and residual confounding. We recommend LS-CM as an alternative to LS-PSM in studies with small sample sizes or limited covariate overlap.

Project description:BackgroundOvertreatment of papillary thyroid microcarcinoma (PTMC) has become a common concern. This study aimed to compare clinicopathological features between PTMC and papillary thyroid carcinoma (PTC) and to explore whether surgery can confer significant survival benefits in all patients with PTC or PTMC.MethodsData of 145,951 patients with PTC registered in Surveillance, Epidemiology, and End Results (SEER) database and 8,751 patients with PTC in our institution were retrospectively collected. Patients with tumors less than 10 mm in diameter were classified as PTMC cohort and the rest as PTC cohort. Clinicopathological features between PTMC and PTC were compared on the basis of SEER cohort and validated with institutional data. Survival analysis was conducted to explore the effect of surgery on the prognosis of patients. To minimize potential confounders and selection bias, we performed propensity score matching (PSM) analysis to match more comparable cohorts.ResultsCompared with PTC, PTMC exhibited the following characteristics: more common in women and whites, older age at diagnosis, lower proportion of follicular variants, intraglandular dissemination, extraglandular and capsular invasion, higher proportion of multifocality, fewer lymph node and distant metastases, and higher cancer-specific survival (CSS) and overall survival (OS) (all p-value < 0.05). Regarding treatment, patients with PTMC received a lower proportion of radiotherapy, chemotherapy, and total thyroidectomy but a higher proportion of lobectomy and/or isthmectomy. There was no significant difference in CSS for patients with PTMC at stage T1N0M0 with or without surgery (P = 0.36).ConclusionGenerally, PTMC showed higher biological indolence than PTC, which meant a higher survival rate for patients in both OS and CSS. For patients with PTMC at staged T1N0M0, active surveillance (AS) may be a potentially feasible management strategy. However, the maintenance of good medical compliance and the management of psychological burden cannot be ignored for patients included in AS.

Dataset Information

Using probabilistic record linkage and propensity-score matching to identify a community-based comparison population.

Publications

Using probabilistic record linkage and propensity-score matching to identify a community-based comparison population.

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