Use of the Sentinel System to Examine Medical Product Use and Outcomes During Pregnancy.

While many pregnant individuals use prescription medications, evidence supporting product safety during pregnancy is often inadequate. Existing electronic healthcare data sources provide large, diverse samples of health plan members to allow for the study of medical product utilization during pregnancy, as well as pregnancy, maternal, and infant outcomes. The Sentinel System is a national medical product surveillance system that includes administrative claims and electronic health record databases from large national and regional health insurers. In addition to these data sources, Sentinel develops and maintains a sizeable selection of analytic tools to facilitate epidemiologic analyses in a way that protects patient privacy and health system autonomy. In this article, we provide an overview of Sentinel System infrastructure, including the Mother-Infant Linkage Table, parameterizable analytic tools, and algorithms to estimate gestational age and identify pregnancy outcomes. We also describe past and future Sentinel work that contributes to our understanding of the way medical products are used and the safety of these products during pregnancy.

Assessing the risk of intentional self-harm in montelukast users: an updated Sentinel System analysis using ICD-10 coding.

BACKGROUND: Montelukast prescribing information includes a Boxed Warning issued in March 2020 regarding neuropsychiatric adverse events. A previous Sentinel System study of asthma patients from 2000 to 2015 did not demonstrate an increased risk of intentional self-harm measured using the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes, with montelukast compared to inhaled corticosteroids (ICS). METHODS: Using a new user cohort study design, we examined intentional self-harm events in patients aged 10 years and older who were incident users of either montelukast or ICS as monotherapy, with a diagnosis of asthma, between October 1, 2015, to June 30, 2022, in the Sentinel System. We measured intentional self-harm using ICD-10-CM codes, which may have better accuracy for capturing suicide attempts than ICD-9-CM codes. We used inverse probability of treatment weighting to balance baseline covariates. We performed subgroup analyses by age group, sex, psychiatric history, and pre/post Boxed Warning era and conducted sensitivity analyses varying type of care setting of the outcome and exposure episode gaps. RESULTS: Among 752,230 and 724,855 patients in the montelukast and ICS exposure groups respectively, we found no association between montelukast use and self-harm compared to ICS use [Hazard Ratio (95% Confidence Interval): 0.96 (0.85, 1.08)]. This finding was consistent across all subgroups, and sensitivity analyses. CONCLUSION: Our results cannot exclude other neuropsychiatric idiosyncratic reactions to montelukast. Compared to the previous Sentinel study, this study identified about double the rate of self-harm events, suggesting a greater sensitivity of ICD-10 codes for measuring self-harm than ICD-9.

Switching patterns of immediate-release forms of generic mixed amphetamine salts products among privately and publicly insured individuals aged 15-64 years in the United States, 2013-2019.

PURPOSE: Immediate-release forms of generic mixed amphetamine salts (MAS) have been the subject of passive surveillance reports signaling lack of effectiveness. We examined switching patterns that might suggest whether long-term users of specific MAS are more likely to switch away or switch back after use of the MAS of interest in the FDA's Sentinel Distributed Database. METHODS: We required at least 60-day continuous supply of selected MAS grouped by Abbreviated New Drug Application (ANDA) to describe patterns of switching away from and to generics approved under the ANDAs of interest among individuals ages 15-64 years with attention deficit hyperactivity disorder or narcolepsy during 2013-2019. RESULTS: We observed the greatest number of treatment episodes for ANDA 040422 (n = 525 771), followed by ANDA 202424 (n = 181 693), ANDA 040439 (n = 62 363), ANDA 040440 (n = 21 143), and ANDA 040480 (n = 8792). Of those with switches away from their original ANDA, episodes initiated on generic products under ANDA 040422 (48.6%) and ANDA 202424 (43.0%) were most likely to switch back, while those initiated on generic product under ANDA 040480 were least likely (24.1%). Of those episodes with switches to a generic under an ANDA of interest, about one-third (range 27.1% to 37.0%) switched back to the same product. These switches back had a median time to switch of about 30 days. CONCLUSIONS: These descriptive analyses, although subject to limitations, did not suggest increased switching away or switching back after use of the generics of interest. Continued post-marketing surveillance is warranted.

Assessing medical product safety during pregnancy using parameterizable tools in the sentinel distributed database.

PURPOSE: The US Food and Drug Administration established the Sentinel System to monitor the safety of medical products. A component of this system includes parameterizable analytic tools to identify mother-infant pairs and evaluate infant outcomes to enable the routine monitoring of the utilization and safety of drugs used in pregnancy. We assessed the feasibility of using the data and tools in the Sentinel System by assessing a known association between topiramate use during pregnancy and oral clefts in the infant. METHODS: We identified mother-infant pairs using the mother-infant linkage table from six data partners contributing to the Sentinel Distributed Database from January 1, 2000, to September 30, 2015. We compared mother-infant pairs with first-trimester exposure to topiramate to mother-infant pairs that were topiramate-unexposed or lamotrigine-exposed and used a validated algorithm to identify oral clefts in the infant. We estimated adjusted risk ratios through propensity score stratification. RESULTS: There were 2007 topiramate-exposed and 1 066 086 unexposed mother-infant pairs in the main comparison. In the active-comparator analysis, there were 1996 topiramate-exposed and 2859 lamotrigine-exposed mother-infant pairs. After propensity score stratification, the odds ratio for oral clefts was 2.92 (95% CI: 1.43, 5.93) comparing the topiramate-exposed to unexposed groups and 2.72 (95% CI: 0.75, 9.93) comparing the topiramate-exposed to lamotrigine-exposed groups. CONCLUSIONS: We found an increased risk of oral clefts after topiramate exposure in the first trimester in the Sentinel database. These results are similar to prior published observational study results and demonstrate the ability of Sentinel's data and analytic tools to assess medical product safety in cohorts of mother-infant pairs in a timely manner.

Utility of fertility procedures and prenatal tests to estimate gestational age for live-births and stillbirths in electronic health plan databases.

PURPOSE: Current algorithms to evaluate gestational age (GA) during pregnancy rely on hospital coding at delivery and are not applicable to non-live births. We developed an algorithm using fertility procedures and fertility tests, without relying on delivery coding, to develop a novel GA algorithm in live-births and stillbirths. METHODS: Three pregnancy cohorts were identified from 16 health-plans in the Sentinel System: 1) hospital admissions for live-birth, 2) hospital admissions for stillbirth, and 3) medical chart-confirmed stillbirths. Fertility procedures and prenatal tests, recommended within specific GA windows were evaluated for inclusion in our GA algorithm. Our GA algorithm was developed against a validated delivery-based GA algorithm in live-births, implemented within a sample of chart-confirmed stillbirths, and compared to national estimates of GA at stillbirth. RESULTS: Our algorithm, including fertility procedures and 11 prenatal tests, assigned a GA at delivery to 97.9% of live-births and 92.6% of stillbirths. For live-births (n = 4 701 207), it estimated GA within 2 weeks of a reference delivery-based GA algorithm in 82.5% of pregnancies, with a mean difference of 3.7 days. In chart-confirmed stillbirths (n = 49), it estimated GA within 2 weeks of the clinically recorded GA at delivery for 80% of pregnancies, with a mean difference of 11.1 days. Implementation of the algorithm in a cohort of stillbirths (n = 40 484) had an increased percentage of deliveries after 36 weeks compared to national estimates. CONCLUSIONS: In a population of primarily commercially-insured pregnant women, fertility procedures and prenatal tests can estimate GA with sufficient sensitivity and accuracy for utility in pregnancy studies.

Risk of hospitalized depression and intentional self-harm with brand and authorized generic sertraline.

BACKGROUND: Recent suggestions of therapeutic inequivalence of brand and generic sertraline have raised concerns about disproportionately higher adverse events among generic users. OBJECTIVE: To assess the impact of confounding in a comparison of the risks of worsening depression and intentional self-harm (ISH) between users of brand name sertraline and its pharmaceutically equivalent authorized generic (AG). METHODS: Using a retrospective new-user cohort design, we identified patients with a diagnosis code for depression aged ≥12 years who were continuously enrolled in a Sentinel Data Partner health plan for ≥180 days before their first sertraline dispensing between June 30, 2006 and September 30, 2015. New use was defined as no evidence of sertraline dispensing in the 180 days before index date. We matched each brand name user to up to 10 AG users using propensity scores (PS) and conducted case-centered logistic regression to assess the risks of hospitalized depression and ISH. RESULTS: Before PS matching, brand name users were significantly less likely to be hospitalized for depression [Hazard Ratio (HR) = 0.70 (95% confidence interval (CI): 0.53-0.94)]. However, in the matched analysis, we observed no statistical difference between brand and AG users [HR = 0.84 (95% CI: 0.59-1.21)]. The risk of ISH did not significantly differ between the exposure groups in unmatched (HR = 0.99 (95% CI: 0.60-1.62) and matched analyses [HR = 0.91 (95% CI: 0.49-1.70). CONCLUSION: In depressed patients receiving brand versus AG sertraline, patient characteristics confounded the association with hospitalization. Baseline differences were ameliorated by PS matching resulting in no statistical difference between brand and AG sertraline users.

Validity of ICD-10-CM diagnoses to identify hospitalizations for serious infections among patients treated with biologic therapies.

PURPOSE: Identifying hospitalizations for serious infections among patients dispensed biologic therapies within healthcare databases is important for post-marketing surveillance of these drugs. We determined the positive predictive value (PPV) of an ICD-10-CM-based diagnostic coding algorithm to identify hospitalization for serious infection among patients dispensed biologic therapy within the FDA's Sentinel Distributed Database. METHODS: We identified health plan members who met the following algorithm criteria: (1) hospital ICD-10-CM discharge diagnosis of serious infection between July 1, 2016 and August 31, 2018; (2) either outpatient/emergency department infection diagnosis or outpatient antimicrobial treatment within 7 days prior to hospitalization; (3) inflammatory bowel disease, psoriasis, or rheumatological diagnosis within 1 year prior to hospitalization, and (4) were dispensed outpatient biologic therapy within 90 days prior to admission. Medical records were reviewed by infectious disease clinicians to adjudicate hospitalizations for serious infection. The PPV (95% confidence interval [CI]) for confirmed events was determined after further weighting by the prevalence of the type of serious infection in the database. RESULTS: Among 223 selected health plan members who met the algorithm, 209 (93.7% [95% CI, 90.1%-96.9%]) were confirmed to have a hospitalization for serious infection. After weighting by the prevalence of the type of serious infection, the PPV of the ICD-10-CM algorithm identifying a hospitalization for serious infection was 80.2% (95% CI, 75.3%-84.7%). CONCLUSIONS: The ICD-10-CM-based algorithm for hospitalization for serious infection among patients dispensed biologic therapies within the Sentinel Distributed Database had 80% PPV for confirmed events and could be considered for use within pharmacoepidemiologic studies.

Trends and Characteristics of the US Adult Population's Behavioral Patterns in Web-Based Prescription Filling: National Survey Study.

BACKGROUND: Filling a prescription on the web has become an alternative to in-person pharmacies for individuals to access their medications. However, the adoption of web-based filling has been gradual, and the use patterns remain to be unclear. OBJECTIVE: This study aims to estimate the trend and prevalence of web-based prescription-filling behavior and identify associated factors among adults in the United States. METHODS: We used data from the US National Health Interview Survey (NHIS) from 2009 to 2018. Adult respondents (aged ≥18 years and over) self-reported their behavior of web-based prescription filling, which was defined as having filled a prescription using the internet in the past 12 months during the survey year. We reported trends using weighted percentages adjusted by the NHIS complex sampling design. We used descriptive statistics and multivariable logistic regression models to examine trends and identify factors associated with web-based prescription-filling behavior. RESULTS: The estimated number of adults reporting web-based prescription-filling behavior significantly increased from 13,319,877 (13,319,877/225,217,942, 5.91%) in 2009 to 28,308,262 (28,308,262/246,611,125, 11.48%) in 2018 (P<.001). Those who were more likely to report filling a prescription on the web were aged between 35 and 74 years, female, White, and frequent users of the computer or internet; these adults also reported higher education, higher income, insurance coverage, and poorer health status. CONCLUSIONS: Web-based prescription-filling behavior among US adults has increased significantly from 2009 to 2018. Health care providers should be aware of the upward trend in the use of web-based pharmacies and ensure the clinical safety of web-based prescriptions.

Patient Knowledge of Safe Use of ER/LA Opioid Analgesics Following Implementation of the Class-Wide REMS: A Survey Study.

BACKGROUND/RATIONALE: The US Food and Drug Administration (FDA) approved a Risk Evaluation and Mitigation Strategy (REMS) for extended release/long-acting (ER/LA) opioids in 2012. The purpose of this study was to assess patient knowledge of the safe use of these products following implementation of the REMS and to determine possible effects of the REMS, including impact on medication access. OBJECTIVE: To assess patient knowledge of safe use of ER/LA opioids and use of REMS patient education tools such as the Medication Guide (MG) and Patient Counseling Document (PCD). METHODS: This was a cross-sectional survey of commercially insured (Commercial) and Medicare Advantage-insured (Medicare) adults with ≥1 pharmacy claim for an ER/LA opioid (10/01/2015 - 02/28/2017) in the HealthCore Integrated Research Database and Medicaid-insured (Medicaid) adult members of a research panel, about their knowledge of safe use of ER/LA opioids and receipt/comprehension of the MG and PCD. RESULTS: Survey respondents consisted of 382 Commercial, 43 Medicare and 40 Medicaid adults. While ≥95% of respondents received and read the MG, fewer were aware of the PCD (Commercial: 47%, Medicare: 65%, Medicaid: 53%). Almost 75% of the knowledge questions were answered correctly by ≥80% of all respondents; fewer respondents recognized that use of opioids as directed can lead to death (Commercial: 73%, Medicare: 56%, Medicaid: 63%), the MG should be read at each dispensing (Commercial: 78%, Medicare: 53%, Medicaid: 75%), opioids should not be stored in the medicine cabinet (Commercial: 77%, Medicare: 79%, Medicaid: 58%), missed doses should not be taken as soon as possible (Commercial: 56%, Medicare: 51%, Medicaid: 50%), and pills should not be crushed (Commercial: 85%, Medicare: 67%, Medicaid: 52%). CONCLUSION: Although most respondents reported reading and understanding the MG and exhibited knowledge of safe use of ER/LA opioids, providers' use of the PCD and increased understanding of safe use core messages need reinforcement.

Risk of Psychiatric Adverse Events Among Montelukast Users.

BACKGROUND: There have been conflicting results from observational studies regarding the risk of psychiatric adverse events (PAEs) with montelukast use. OBJECTIVE: To determine whether there are associations of depressive disorders, self-harm, and suicide with use of montelukast compared with inhaled corticosteroid (ICS) use. METHODS: Using data from the Sentinel Distributed Database from January 1, 2000, to September 30, 2015, patients (n = 457,377) exposed to montelukast or ICS, aged 6 years and older with a diagnosis of asthma, were matched 1:1 on propensity scores. Hazard ratios (HRs) and 95% CIs were estimated for each study outcome overall and by age, sex, psychiatric history, and pre-/post-2008 labeling updates using Cox proportional hazards regression models. RESULTS: Exposure to montelukast was associated with a lower risk of treated outpatient depressive disorder (HR, 0.91; 95% CI, 0.89-0.93). No increased risks of inpatient depressive disorder (HR, 1.06; 95% CI, 0.90-1.24), self-harm (HR, 0.92; 95% CI, 0.69-1.21), or self-harm using a modified algorithm (HR, 0.81; 95% CI, 0.63-1.05) were observed with montelukast use compared with ICS use. Most PAEs occurred in the roughly one-third of patients having a past psychiatric history. CONCLUSIONS: When compared with use of ICS, we did not find associations between montelukast use and hospitalizations for depression or self-harm events. Our findings should be interpreted considering the study's limitations. Psychiatric comorbidity was common, and most PAEs occurred in patients with a past psychiatric history.

Health information technology use among older adults in the United States, 2009-2018.

Objectives: The purpose of this study was to assess (1) the trends of and (2) the factors associated with health information technology (HIT) use among older adults in the U.S.Methods: A decade (2009-2018) of data from the U.S. National Health Interview Survey (NHIS) was used. The trends of HIT use among older adults (aged 65 over) were reported and compared to younger adults (aged 18-64) using weighted percentages adjusted by NHIS complex sampling design. HIT use, which was assessed with five questions asking whether respondents used the internet to (1) look up health information, (2) use chat groups to learn about health topics, (3) fill a prescription, (4) schedule medical appointments, and (5) communicate with health care providers by email. Andersen's Behavioral Model of Health Services Use was used to select and categorize the covariates. Multivariable logistic regression models were conducted to identify the predictors of HIT use.Results: The prevalence of HIT use significantly increased from 9.3 million (24.8% of the 37.3 million older adults) in 2009 to 22.3 million (43.9% of the 50.9 million older adults) in 2018 (p < .01). Among U.S. older adults, young-older, white females, higher education, higher income, insurance coverage, and good health status were more likely to report HIT use.Conclusions: This study found an increasing trend of HIT use among older adults in the U.S. from 2009 to 2018. Healthcare providers should be conscious of older adults' increased HIT use patterns and guide them to proper health management.

Incidence of Opioid Overdose Among Patients Using ER/LA Opioid Analgesics Before and After Implementation of the Class-Wide Opioid Risk Evaluation and Mitigation Strategy.

INTRODUCTION: The United States (US) Food and Drug Administration (FDA) required a Risk Evaluation and Mitigation Strategy (REMS) for extended-release and long-acting (ER/LA) opioid analgesics on 09 July 2012. METHODS: This study compared the incidence of opioid overdose before (July 2010-June 2012) and after (July 2013-September 2016) the initiation of the Risk Evaluation and Mitigation Strategy (REMS) for extended-release and long-acting (ER/LA) opioid analgesics. We identified patients with ≥1 ER/LA opioid dispensing in either time period in national data from the HealthCore Integrated Research DatabaseSM (HIRD) and in United States (US) Medicaid claims data from four states. We described each population, calculated the incidence rate (IR) of opioid overdose, and assessed crude and propensity score adjusted incidence rate ratios (IRR) comparing the overdose rate after vs before implementation of the REMS. RESULTS: A total of 121,229 commercially insured and 11,488 Medicaid patients were included in the analysis. Rates of overdose were substantially higher in Medicaid patients than in the commercially insured patients (IR 192.0, 95% confidence interval [CI] 162.60-225.18 versus 102.60, 95% CI 93.0-112.93 in the active period). The IRRs for opioid overdose were 1.01 (95% CI 0.87-1.17) in the commercially insured population and 0.70 (95% CI 0.52-0.93) in Medicaid. CONCLUSION: This leveling off of overdose rates among commercially insured patients and decline among Medicaid patients is encouraging, but it is difficult to disentangle the specific impact of the REMS from many other ongoing initiatives with similar goals.

Understanding utilization patterns of biologics and biosimilars in the United States to support postmarketing studies of safety and effectiveness.

PURPOSE: To describe utilization of filgrastim and infliximab, the first two products with biosimilars approved in the United States. METHODS: We identified use of filgrastim (reference, tbo-filgrastim, and filgrastim-sndz) and infliximab (reference, infliximab-dyyb, and infliximab-abda) in the Sentinel Distributed Database using Healthcare Common Procedure Coding System (HCPCS) codes and National Drug Codes (NDCs) from January 2015 to August 2018. We calculated the proportion of use by code type and assessed uptake over time. We compared baseline patient characteristics and treatment indications. Among patients with >1 exposure episode, we characterized gaps between episodes. RESULTS: Use was identified primarily via HCPCS codes (filgrastim: 86.4%-97.7%; infliximab: 87.8%-100%) although some was identified via NDCs (filgrastim: 2.2%-13.5%; infliximab: <0.1%-6.5%). Filgrastim reference product use declined from 89.4% in January 2015 to 30.3% in June 2018, with corresponding increases in filgrastim-sndz (0% to 49.3%) and tbo-filgrastim (10.6% to 20.4%). Infliximab biosimilar uptake was low (9.7% in June 2018). We identified 94 846 filgrastim reference product, 27 143 tbo-filgrastim, and 38 264 filgrastim-sndz users. For infliximab, we identified 125 412 reference product, 1034 infliximab-dyyb, 49 infliximab-abda, and 4855 undetermined biosimilar users. Patients receiving filgrastim products were largely similar, but differences in age, sex, and indication were observed across infliximab product users. The median exposure episode gap ranged from 1 to 3 days for filgrastim and 48 to 50 days for infliximab. CONCLUSION: Use of biosimilar filgrastim has increased in the United States, but infliximab biosimilar use remains low. Data on identification of biosimilars in claims data and observed gaps between exposure episodes can be used to support drug safety studies of biosimilars.

Medical record-based ascertainment of behaviors suggestive of opioid misuse, diversion, abuse, and/or addiction among individuals showing evidence of doctor/pharmacy shopping.

OBJECTIVES: Doctor/pharmacy shopping, the practice of seeking prescriptions from multiple healthcare sources without their coordination, may be a measure of prescription medicine abuse. This cross-sectional study examined the relationship between a claims-based doctor/pharmacy shopping definition and medical record documented behaviors suggestive of misuse, diversion, abuse and/or addiction. METHODS: Patients with ≥2 opioid dispensings starting in 2012 in a US administrative claims database were grouped into doctor/pharmacy shopping categories by number of providers and pharmacies used over 18 months: no shopping, minimal shopping, moderate shopping and severe shopping. Medical charts of opioid prescribers were reviewed to identify behaviors suggestive of misuse, diversion, abuse and/or addiction. RESULTS: Among 581,940 opioid users, 78% were classified as no shopping, 11% minimal shopping, 8% moderate shopping and 3% severe shopping. Almost 40% of severe shopping patients had no medical record documented behaviors (positive predictive value: 24.3%). Compared with no shopping, the odds ratio [OR] of ≥3 behaviors was 1.70 (95% confidence interval [CI] 0.50-5.78) for minimal shopping, 1.81 (95% CI 0.54-6.03) for moderate shopping, and 8.93 (95% CI 3.12-25.54) for severe shopping. CONCLUSIONS: Claims-identified severe doctor/pharmacy shopping was strongly associated with behaviors suggestive of misuse, diversion, abuse and/or addiction, but the proportion of medical records documenting these was low.

Development of predictive models to identify advanced-stage cancer patients in a US healthcare claims database.

BACKGROUND: Although healthcare databases are a valuable source for real-world oncology data, cancer stage is often lacking. We developed predictive models using claims data to identify metastatic/advanced-stage patients with ovarian cancer, urothelial carcinoma, gastric adenocarcinoma, Merkel cell carcinoma (MCC), and non-small cell lung cancer (NSCLC). METHODS: Patients with ≥1 diagnosis of a cancer of interest were identified in the HealthCore Integrated Research Database (HIRD), a United States (US) healthcare database (2010-2016). Data were linked to three US state cancer registries and the HealthCore Integrated Research Environment Oncology database to identify cancer stage. Predictive models were constructed to estimate the probability of metastatic/advanced stage. Predictors available in the HIRD were identified and coefficients estimated by Least Absolute Shrinkage and Selection Operator (LASSO) regression with cross-validation to control overfitting. Classification error rates and receiver operating characteristic curves were used to select probability thresholds for classifying patients as cases of metastatic/advanced cancer. RESULTS: We used 2723 ovarian cancer, 6522 urothelial carcinoma, 1441 gastric adenocarcinoma, 109 MCC, and 12,373 NSCLC cases of early and metastatic/advanced cancer to develop predictive models. All models had high discrimination (C > 0.85). At thresholds selected for each model, PPVs were all >0.75: ovarian cancer = 0.95 (95% confidence interval [95% CI]: 0.94-0.96), urothelial carcinoma = 0.78 (95% CI: 0.70-0.86), gastric adenocarcinoma = 0.86 (95% CI: 0.83-0.88), MCC = 0.77 (95% CI 0.68-0.89), and NSCLC = 0.91 (95% CI 0.90 - 0.92). CONCLUSION: Predictive modeling was used to identify five types of metastatic/advanced cancer in a healthcare claims database with greater accuracy than previous methods.

Patient and prescriber characteristics among patients with type 2 diabetes mellitus continuing or discontinuing sulfonylureas following insulin initiation: data from a large commercial database.

OBJECTIVE: To describe patient and provider characteristics for patients with type 2 diabetes (T2DM) initiating basal insulin and describe basal insulin's impact on sulfonylurea (SU) discontinuation. METHODS: A retrospective cohort study was conducted using the HealthCore Integrated Research Database. Patients had ≥12 months of continuous coverage prior to initiating insulin, and were utilizing at least one anti-hyperglycemic drug at the time of insulin initiation. Predictors for SU discontinuation were evaluated utilizing Cox proportional hazards models. RESULTS: Among the 74,334 individuals aged ≥18 years with T2DM who initiated basal insulin from 2006-2015, 30% were taking metformin (MET) and SU when initiating insulin. Among the 22,418 MET/SU patients, 31% discontinued SU within 3 months of insulin initiation and, by 12 months, 55% had discontinued SU. Sulfonylurea discontinuation was similar among many patient and provider characteristics, while being modestly positively associated (p < .05; HRs <1.5) with female gender, more co-morbidities, cardiac revascularization, chronic liver disease, hospitalizations with a T2DM diagnosis, and hypoglycemia prior to insulin initiation. SU discontinuation was modestly inversely associated with receiving an insulin prescription from an endocrinologist (HR = 0.90, 95% CI = 0.85-0.95). CONCLUSIONS: Roughly half of commercially-insured T2DM patients discontinued SU within 1 year after insulin initiation, and SU discontinuation was not strongly associated with a range of patient and provider characteristics.

Bone Loss at the Hip and Subsequent Mortality in Older Men: The Osteoporotic Fractures in Men (MrOS) Study.

Low bone mineral density (BMD) is associated with increased mortality risk, yet the impact of BMD loss on mortality is relatively unknown. We hypothesized that greater BMD loss is associated with increased mortality risk in older men. Change in femoral neck BMD was assessed in 4400 Osteoporotic Fractures in Men (MrOS) study participants with two to three repeat dual-energy X-ray absorptiometry scans over an average of 4.6 ± 0.4 (mean ± SD) years. Change in femoral neck BMD was estimated using mixed effects models; men were grouped into three categories of BMD change: maintenance (n = 1087; change ≥ 0 g/cm2); expected loss (n = 2768; change between 0 g/cm2 and <1 SD below mean change [>-0.034 g/cm2]); and accelerated loss (n = 545; change 1 SD below mean change or worse [≤-0.034 g/cm2]). Multivariate proportional hazards models adjusted for potential confounders estimated the risk of all-cause mortality over 8.1 ± 2.8 years following visit 2. Mortality was centrally adjudicated by physician review of death certificates. At visit 1, mean age was 72.9 ± 5.5 years. Men who maintained BMD were less likely to die during the subsequent follow-up period (33.7%) than men who had accelerated BMD loss (60.6%) (p < 0.001). Compared to men who had maintained BMD, those who had accelerated BMD loss had a 44% greater risk of mortality in multivariate-adjusted models (HR, 1.44; 95% CI, 1.23 to 1.68). Compared to men who had maintained BMD, there was no significant difference in mortality risk for men with expected loss of BMD (36.9% died) (multivariate HR, 1.00; 95% CI, 0.89 to 1.13). Further adjustment for visit 1 or visit 2 BMD measurement did not substantially alter these associations. Results for total hip BMD were similar. In conclusion, accelerated loss of BMD at the hip is a risk factor for mortality in men that is not explained by comorbidity burden, concurrent change in weight, or physical activity.

Impact of Competing Risk of Mortality on Association of Weight Loss With Risk of Central Body Fractures in Older Men: A Prospective Cohort Study.

To determine the association of weight loss with risk of clinical fractures at the hip, spine, and pelvis (central body fractures [CBFs]) in older men with and without accounting for the competing risk of mortality, we used data from 4523 men (mean age 77.5 years). Weight change between baseline and follow-up (mean 4.5 years between examinations) was categorized as moderate loss (loss ≥10%), mild loss (loss 5% to <10%), stable (<5% change) or gain (gain ≥5%). Participants were contacted every 4 months after the follow-up examination to ascertain vital status (deaths verified by death certificates) and ask about fractures (confirmed by radiographic reports). Absolute probability of CBF by weight change category was estimated using traditional Kaplan-Meier method and cumulative incidence function accounting for competing mortality risk. Risk of CBF by weight change category was determined using conventional Cox proportional hazards regression and subdistribution hazards models with death as a competing risk. During an average of 8 years, 337 men (7.5%) experienced CBF and 1569 (34.7%) died before experiencing this outcome. Among men with moderate weight loss, CBF probability was 6.8% at 5 years and 16.9% at 10 years using Kaplan-Meier versus 5.7% at 5 years and 10.2% at 10 years using a competing risk approach. Men with moderate weight loss compared with those with stable weight had a 1.6-fold higher adjusted risk of CBF (HR 1.59; 95% CI, 1.06 to 2.38) using Cox models that was substantially attenuated in models accounting for competing mortality risk and no longer significant (subdistribution HR 1.16; 95% CI, 0.77 to 1.75). Results were similar in analyses substituting hip fracture for CBF. Older men with weight loss who survive are at increased risk of CBF, including hip fracture. However, ignoring the competing mortality risk among men with weight loss substantially overestimates their long-term fracture probability and relative fracture risk. © 2016 American Society for Bone and Mineral Research.

Slow Gait Speed and Risk of Long-Term Nursing Home Residence in Older Women, Adjusting for Competing Risk of Mortality: Results from the Study of Osteoporotic Fractures.

OBJECTIVES: To determine whether slow gait speed increases the risk of costly long-term nursing home residence when accounting for death as a competing risk remains unknown. DESIGN: Longitudinal cohort study using proportional hazards models to predict long-term nursing home residence and subdistribution models with death as a competing risk. SETTING: Community-based prospective cohort study. PARTICIPANTS: Older women (mean age 76.3) participating in the Study of Osteoporotic Fractures who were also enrolled in Medicare fee-for-service plans (N = 3,755). MEASUREMENTS: Gait speed was measured on a straight 6-m course and averaged over two trials. Long-term nursing home residence was defined using a validated algorithm based on Medicare Part B claims for nursing home-related care. RESULTS: Participants were followed until long-term nursing home residence, disenrollment from Medicare plan, death, or December 31, 2010. Over the follow-up period (median 11 years), 881 participants (23%) experienced long-term nursing home residence, and 1,013 (27%) died before experiencing this outcome. Slow walkers (55% of participants with gait speed <1 m/s) were significantly more likely than fast walkers to reside in a nursing home long-term (adjusted hazards ratio (aHR) = 1.79, 95% confidence interval (CI) = 1.54-2.09). Associations were attenuated in subdistribution models (aHR = 1.52, 95% CI = 1.30-1.77) but remained statistically significant. CONCLUSION: Older community-dwelling women with slow gait speed are more likely to experience long-term nursing home residence, as well as mortality without long-term residence. Ignoring the competing mortality risk may overestimate long-term care needs and costs.

The Relationship Between Caregiving and Mortality After Accounting for Time-Varying Caregiver Status and Addressing the Healthy Caregiver Hypothesis.

BACKGROUND: Previous studies have shown inconsistent associations between caregiving and mortality. This may be due to analyzing caregiver status at baseline only, and that better health is probably related to taking on caregiving responsibilities and continuing in that role. The latter is termed The Healthy Caregiver Hypothesis, similar to the Healthy Worker Effect in occupational epidemiology. We applied common approaches from occupational epidemiology to evaluate the association between caregiving and mortality, including treating caregiving as time-varying and lagging exposure up to 5 years. METHODS: Caregiving status among 1,068 women (baseline mean age = 81.0 years; 35% caregivers) participating in the Caregiver-Study of Osteoporotic Fractures study was assessed at five interviews conducted between 1999 and 2009. Mortality was determined through January 2012. Cox proportional hazards models were used to estimate adjusted hazard ratios and 95% confidence intervals adjusted for sociodemographics, perceived stress, and functional limitations. RESULTS: A total of 483 participants died during follow-up (38.8% and 48.7% of baseline caregivers and noncaregivers, respectively). Using baseline caregiving status, the association with mortality was 0.77, 0.62-0.95. Models of time-varying caregiving status showed a more pronounced reduction in mortality in current caregivers (hazard ratios = 0.54, 0.38-0.75), which diminished with longer lag periods (3-year lag hazard ratio = 0.68, 0.52-0.88, 5-year lag hazard ratios = 0.76, 0.60-0.95). CONCLUSIONS: Overall, caregivers had lower mortality rates than noncaregivers in all analyses. These associations were sensitive to the lagged period, indicating that the timing of leaving caregiving does influence this relationship and should be considered in future investigations.