Background Recent postmarketing trials produced conflicting results about the risk for hospitalized heart failure (hHF) associated with dipeptidyl peptidase-4 (DPP-4) inhibitors, creating uncertainty about the safety of these antihyperglycemic agents. Objective To examine the associations of hHF with saxagliptin and sitagliptin. Design Population-based, retrospective, new-user cohort study. Setting 18 health insurance and health system data partners in the U.S. Food and Drug Administration’s Mini-Sentinel program. Patients Patients aged 18 years or older with type 2 diabetes who initiated therapy with saxagliptin, sitagliptin, pioglitazone, second-generation sulfonylureas, or long-acting insulin products from 2006 to 2013. Measurements Hospitalized HF, identified by International Classification of Diseases, Ninth Revision, Clinical Modification codes 402.×1, 404.×1, 404.×3, and 428.×× recorded as the principal discharge diagnosis. Results 78 553 saxagliptin users and 298 124 sitagliptin users contributed an average of 7 to 9 months of follow-up data to 1 or more pairwise comparisons. The risk for hHF was not higher with DPP-4 inhibitors than with the other study drugs. The hazard ratios from the disease risk score (DRS)–stratified analyses were 0.83 (95% CI, 0.70 to 0.99) for saxagliptin versus sitagliptin, 0.63 (CI, 0.47 to 0.85) for saxagliptin versus pioglitazone, 0.69 (CI, 0.54 to 0.87) for saxagliptin versus sulfonylureas, and 0.61 (CI, 0.50 to 0.73) for saxagliptin versus insulin. The DRS-stratified hazard ratios were 0.74 (CI, 0.64 to 0.85) for sitagliptin versus pioglitazone, 0.86 (CI, 0.77 to 0.95) for sitagliptin versus sulfonylureas, and 0.71 (CI, 0.64 to 0.78) for sitagliptin versus insulin. Results from the 1:1 propensity score–matched analyses were similar. Results were also similar in subgroups of patients with and without prior cardiovascular disease and in a subgroup defined by the 2 highest DRS deciles. Limitation Residual confounding and short follow-up. Conclusion In this large cohort study, a higher risk for hHF was not observed in users of saxagliptin or sitagliptin compared with other selected antihyperglycemic agents. Primary Funding Source U.S. Food and Drug Administration.
Purpose To validate an algorithm based upon International Classification of Diseases, 9th revision, Clinical Modification (ICD-9-CM) codes for acute myocardial infarction (AMI) documented within the Mini-Sentinel Distributed Database (MSDD). Methods Using an ICD-9-CM-based algorithm (hospitalized patients with 410.x0 or 410.x1 in primary position), we identified a random sample of potential cases of AMI in 2009 from 4 Data Partners participating in the Mini-Sentinel Program. Cardiologist reviewers used information abstracted from hospital records to assess the likelihood of an AMI diagnosis based on criteria from the joint European Society of Cardiology and American College of Cardiology Global Task Force. Positive predictive values (PPVs) of the ICD-9-based algorithm were calculated. Results Of the 153 potential cases of AMI identified, hospital records for 143 (93%) were retrieved and abstracted. Overall, the PPV was 86.0% (95% confidence interval; 79.2%, 91.2%). PPVs ranged from 76.3% to 94.3% across the 4 Data Partners. Conclusions The overall PPV of potential AMI cases, as identified using an ICD-9-CM-based algorithm, may be acceptable for safety surveillance; however, PPVs do vary across Data Partners. This validation effort provides a contemporary estimate of the reliability of this algorithm for use in future surveillance efforts conducted using the FDA’s MSDD.
Purpose The validity of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes to identify diagnoses of severe acute liver injury (SALI) is not well known. We examined the positive predictive values (PPVs) of hospital ICD-9-CM diagnoses in identifying SALI among health plan members in the Mini-Sentinel Distributed Database (MSDD) for patients without liver/biliary disease and for those with chronic liver disease (CLD). Methods We selected random samples of members (149 without liver/biliary disease; 75 with CLD) with a principal hospital diagnosis suggestive of SALI (ICD-9-CM 570, 572.2, 572.4, 572.8, 573.3, 573.8, or V42.7) in the MSDD (2009–2010). Medical records were reviewed by hepatologists to confirm SALI events. PPVs of codes and code combinations for confirmed SALI were determined by CLD status. Results Among 105 members with available records and no liver/biliary disease, SALI was confirmed in 26 (PPV, 24.7%; 95% CI, 16.9% – 34.1%). Combined hospital diagnoses of acute hepatic necrosis (570) and liver disease sequelae (572.8) had high PPV (100%; 95% CI, 59.0% – 100%) and identified 7/26 (26.9%) events. Among 46 CLD members with available records, SALI was confirmed in 19 (PPV, 41.3%; 95% CI, 27.0% – 56.8%). Acute hepatic necrosis (570) or hepatorenal syndrome (572.4) plus any other SALI code had a PPV of 83.3% (95% CI, 51.6% – 97.9%) and identified 10/19 (52.6%) events. Conclusions Most individual hospital ICD-9-CM diagnoses had low PPV for confirmed SALI events. Select code combinations had high PPV but did not capture all events.
EHR-based, triggered ADE reporting is efficient and acceptable to clinicians, provides detailed clinical information, and has the potential to greatly increase the number and quality of spontaneous reports submitted to the FDA.
The US Food and Drug Administration's Sentinel system has developed the capability to conduct active safety surveillance of marketed medical products in a large network of electronic healthcare databases. We assessed the extent to which the newly developed, semiautomated Sentinel Propensity Score Matching (PSM) tool could produce the same results as a customized protocol-driven assessment, which found an adjusted hazard ratio (HR) of 3.04 (95% confidence interval [CI], 2.81-3.27) comparing angioedema in patients initiating angiotensin-converting enzyme (ACE) inhibitors vs. beta-blockers. Using data from 13 Data Partners between 1 January 2008, and 30 September 2013, the PSM tool identified 2,211,215 eligible ACE inhibitor and 1,673,682 eligible beta-blocker initiators. The tool produced an HR of 3.14 (95% CI, 2.86-3.44). This comparison provides initial evidence that Sentinel analytic tools can produce findings similar to those produced by a highly customized protocol-driven assessment.
Purpose To describe the Acute Myocardial Infarction (AMI) Validation project, a test case for health outcome validation within the FDA-funded Mini-Sentinel pilot program. Methods The project consisted of four parts: (1) case identification: developing an ICD9-based algorithm to identify hospitalized AMI patients within the Mini-Sentinel Distributed Database; (2) chart retrieval: establishing procedures that ensured patient privacy (collection and transfer of minimum necessary amount of information, and redaction of direct identifiers to validate potential cases of AMI; (3) abstraction and adjudication: trained nurse abstractors gathered key data using a standardized form with cardiologist adjudication; and (4) calculation of the positive predictive value of the constructed algorithm. Results Key decision points included: (1) breadth of the AMI algorithm; (2) centralized vs. distributed abstraction; and (3) approaches to maintaining patient privacy and to obtaining charts for public health purposes. We used an algorithm limited to ICD9 codes 410.x0-410.x1. Centralized data abstraction was performed due to the modest number of charts requested (<155). The project’s public health status accelerated chart retrieval in most instances. Conclusions We have established a process to validate AMI within Mini-Sentinel, which may be used for other health outcomes. Challenges include: (1) ensuring that only minimum necessary data is transmitted by Data Partners for centralized chart review; (2) establishing procedures to maintain data privacy while still allowing for timely access to medical charts; and (3) securing access to charts for public health uses that do not require IRB approval while maintaining patient privacy.
BACKGROUND: Disparities in treatment and mortality for colorectal cancer (CRC) may reflect differences in access to specialized care or other characteristics of the area where an individual lives. METHODS: Surveillance, Epidemiology and End Results Program-Medicare data for seniors diagnosed with CRC were linked to area measures of the sociodemographic characteristics and the capacity of surgeons, medical oncologists, and radiation oncologists. Outcomes included receipt of stage-appropriate CRC care and mortality. RESULTS: After adjustment, blacks and Hispanics were less likely than whites to undergo surgery (odds ratio [OR] 0.57, 95% confidence interval (CI) 0.52-0.63 and OR 0.82, 95% CI 0.70-0.95, respectively). Individuals who lived in areas with the highest tertile of surgeon capacity were more likely to undergo resection than those in the lowest, and use of surgery declined as the percentage of blacks in the area increased. Adjustment for the area measures resulted in a modest decline in disparities in care relative to whites (5.3% for black). Blacks also experienced greater all-cause and cancer-specific mortality than whites. Further adjustment for area sociodemographics and surgeon capacity reduced the disparity in mortality between blacks and whites. Although there was a similar black/white disparity in the use of adjuvant chemotherapy, the disparity remained after adjustment for area characteristics, although use of chemotherapy was greater in areas with the greatest capacity of medical oncologists. CONCLUSIONS: Sociodemographic characteristics and measures of the availability of specialized cancer providers in the area in which an individual resides modestly mediated disparities in the receipt of CRC care and mortality, suggesting that other factors may also be important. Cancer 2011;117:4267-
The 2005 and 2010 FDA regulatory activities might have contributed to reduced use of LABA agents, as intended; however, their effect, independent of other factors, cannot be determined. Use of other classes of asthma medications was similarly affected.
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