Validation of an electronic algorithm for Hodgkin and non-Hodgkin lymphoma in ICD-10-CM.

PURPOSE: Lymphoma is a health outcome of interest for drug safety studies. Studies using administrative claims data require the accurate identification of lymphoma cases. We developed and validated an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM)-based algorithm to identify lymphoma in healthcare claims data. METHODS: We developed a three-component algorithm to identify patients aged ≥15 years who were newly diagnosed with Hodgkin (HL) or non-Hodgkin (NHL) lymphoma from January 2016 through July 2018 among members of four Data Partners within the FDA's Sentinel System. The algorithm identified potential cases as patients with ≥2 ICD-10-CM lymphoma diagnosis codes on different dates within 183 days; ≥1 procedure code for a diagnostic procedure (e.g., biopsy, flow cytometry) and ≥1 procedure code for a relevant imaging study within 90 days of the first lymphoma diagnosis code. Cases identified by the algorithm were adjudicated via chart review and a positive predictive value (PPV) was calculated. RESULTS: We identified 8723 potential lymphoma cases via the algorithm and randomly sampled 213 for validation. We retrieved 138 charts (65%) and adjudicated 134 (63%). The overall PPV was 77% (95% confidence interval: 69%-84%). Most cases also had subtype information available, with 88% of cases identified as NHL and 11% as HL. CONCLUSIONS: Seventy-seven percent of lymphoma cases identified by an algorithm based on ICD-10-CM diagnosis and procedure codes and applied to claims data were true cases. This novel algorithm represents an efficient, cost-effective way to target an important health outcome of interest for large-scale drug safety and public health surveillance studies.

Prospective influenza vaccine safety surveillance using fresh data in the Sentinel System.

PURPOSE: To develop the infrastructure to conduct timely active surveillance for safety of influenza vaccines and other medical countermeasures in the Sentinel System (formerly the Mini-Sentinel Pilot), a Food and Drug Administration-sponsored national surveillance system that typically relies on data that are mature, settled, and updated quarterly. METHODS: Three Data Partners provided their earliest available ("fresh") cumulative claims data on influenza vaccination and health outcomes 3-4 times on a staggered basis during the 2013-2014 influenza season, collectively producing 10 data updates. We monitored anaphylaxis in the entire population using a cohort design and seizures in children ≤4 years of age using both a self-controlled risk interval design (primary) and a cohort design (secondary). After each data update, we conducted sequential analysis for inactivated (IIV) and live (LAIV) influenza vaccines using the Maximized Sequential Probability Ratio Test, adjusting for data-lag. RESULTS: Most of the 10 sequential analyses were conducted within 6 weeks of the last care-date in the cumulative dataset. A total of 6 682 336 doses of IIV and 782 125 doses of LAIV were captured. The primary analyses did not identify any statistical signals following IIV or LAIV. In secondary analysis, the risk of seizures was higher following concomitant IIV and PCV13 than historically after IIV in 6- to 23-month-olds (relative risk = 2.7), which requires further investigation. CONCLUSIONS: The Sentinel System can implement a sequential analysis system that uses fresh data for medical product safety surveillance. Active surveillance using sequential analysis of fresh data holds promise for detecting clinically significant health risks early. Limitations of employing fresh data for surveillance include cost and the need for careful scrutiny of signals. © 2015 The Authors. Pharmacoepidemiology and Drug Safety Published by John Wiley & Sons Ltd.

Validation of anaphylaxis in the Food and Drug Administration's Mini-Sentinel.

PURPOSE: We aim to develop and validate the positive predictive value (PPV) of an algorithm to identify anaphylaxis using health plan administrative and claims data. Previously published PPVs for anaphylaxis using International Classification of Diseases, ninth revision, Clinical Modification (ICD-9-CM) codes range from 52% to 57%. METHODS: We conducted a retrospective study using administrative and claims data from eight health plans. Using diagnosis and procedure codes, we developed an algorithm to identify potential cases of anaphylaxis from the Mini-Sentinel Distributed Database between January 2009 and December 2010. A random sample of medical charts (n = 150) was identified for chart abstraction. Two physician adjudicators reviewed each potential case. Using physician adjudicator judgments on whether the case met diagnostic criteria for anaphylaxis, we calculated a PPV for the algorithm. RESULTS: Of the 122 patients for whom complete charts were received, 77 were judged by physician adjudicators to have anaphylaxis. The PPV for the algorithm was 63.1% (95%CI: 53.9-71.7%), using the clinical criteria by Sampson as the gold standard. The PPV was highest for inpatient encounters with ICD-9-CM codes of 995.0 or 999.4. By combining only the top performing ICD-9-CM codes, we identified an algorithm with a PPV of 75.0%, but only 66% of cases of anaphylaxis were identified using this modified algorithm. CONCLUSIONS: The PPV for the ICD-9-CM-based algorithm for anaphylaxis was slightly higher than PPV estimates reported in prior studies, but remained low. We were able to identify an algorithm that optimized the PPV but demonstrated lower sensitivity for anaphylactic events.

Validity of diagnostic codes to identify cases of severe acute liver injury in the US Food and Drug Administration's Mini-Sentinel Distributed Database.

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.

The risk of febrile seizures following influenza and 13-valent pneumococcal conjugate vaccines.

BACKGROUND: Evidence on the risk of febrile seizures after inactivated influenza vaccine (IIV) and 13-valent pneumococcal conjugate vaccine (PCV13) is mixed. In the FDA-sponsored Sentinel Initiative, we examined risk of febrile seizures after IIV and PCV13 in children 6-23 months of age during the 2013-14 and 2014-15 influenza seasons. METHODS: Using claims data and a self-controlled risk interval design, we compared the febrile seizure rate in a risk interval (0-1 days) versus control interval (14-20 days). In exploratory analyses, we assessed whether the effect of IIV was modified by concomitant PCV13 administration. RESULTS: Adjusted for age, calendar time and concomitant administration of the other vaccine, the incidence rate ratio (IRR) for risk of febrile seizures following IIV was 1.12 (95% CI 0.80, 1.56) and following PCV13 was 1.80 (95% CI 1.29, 2.52). The attributable risk for febrile seizures following PCV13 ranged from 0.33 to 5.16 per 100,000 doses by week of age. The age and calendar-time adjusted IRR comparing exposed to unexposed time was numerically larger for concomitant IIV and PCV13 (IRR 2.80, 95% CI 1.63, 4.83), as compared to PCV13 without concomitant IIV (IRR 1.54, 95% CI 1.04, 2.28), and the IRR for IIV without concomitant PCV13 suggested no independent effects of IIV (IRR 0.94, 95% CI 0.63, 1.42). Taken together, this suggests a possible interaction between IIV and PCV13, though our study was not sufficiently powered to provide a precise estimate of the interaction. CONCLUSIONS: We found an elevated risk of febrile seizures after PCV13 vaccine but not after IIV. The risk of febrile seizures after PCV13 is low compared to the overall risk in this population of children, and the risk should be interpreted in the context of the importance of preventing pneumococcal infections.

Evaluation of the risk of venous thromboembolism after quadrivalent human papillomavirus vaccination among US females.

After the Food and Drug Administration (FDA) licensed quadrivalent human papillomavirus vaccine (HPV4) in 2006, reports suggesting a possible association with venous thromboembolism (VTE) emerged from the Vaccine Adverse Event Reporting System and the Vaccine Safety Datalink. Our objective was to determine whether HPV4 increased VTE risk. The subjects were 9-26-year-old female members of five data partners in the FDA's Mini-Sentinel pilot project receiving HPV4 during 2006-2013. The outcome was radiologically confirmed first-ever VTE among potential cases identified by diagnosis codes in administrative data during Days 1-77 after HPV4 vaccination. With a self-controlled risk interval design, we compared counts of first-ever VTE in risk intervals (Days 1-28 and Days 1-7 post-vaccination) and control intervals (Days 36-56 for Dose 1 and Days 36-63 for Doses 2 and 3). Combined hormonal contraceptive use was treated as a potential confounder. The main analyses were: (1) unadjusted for time-varying VTE risk from contraceptive use, (2) unadjusted but restricted to cases without such time-varying risk, and (3) adjusted by incorporating the modeled risk of VTE by week of contraceptive use in the analysis. Of 279 potential VTE cases identified following 1,423,399 HPV4 doses administered, 225 had obtainable charts, and 53 were confirmed first-ever VTE. All 30 with onsets in risk or control intervals had known risk factors for VTE. VTE risk was not elevated in the first 7 or 28 days following any dose of HPV in any analysis (e.g. relative risk estimate (95% CI) from both unrestricted analyses, for all-doses, 28-day risk interval: 0.7 (0.3-1.4)). Temporal scan statistics found no clustering of VTE onsets after any dose. Thus, we found no evidence of an increased risk of VTE associated with HPV4 among 9-26-year-old females. A particular strength of this evaluation was its control for both time-invariant and contraceptive-related time-varying potential confounding.

p53 mutations in human aggressive and nonaggressive basal and squamous cell carcinomas.

PURPOSE: The purpose is to investigate whether aggressive basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) differ from nonaggressive BCC and SCC with respect to the p53 mutation spectrum and whether specific mutations can serve as prognostic indicators of tumor aggressiveness. EXPERIMENTAL DESIGN: We analyzed 342 tissues from patients with aggressive and nonaggressive BCCs and SCCs for p53 mutations by single-strand conformation polymorphism and nucleotide sequencing. RESULTS: p53 mutations were detected in 33 of 50 aggressive BCCs (66%), 37 of 98 nonaggressive BCCs (38%), 28 of 80 aggressive SCCs (35%), 28 of 56 nonaggressive SCCs (50%), and 3 of 29 samples of sun-exposed skin (10%). About 71% of the p53 mutations detected in aggressive and nonaggressive BCCs and SCCs were UV signature mutations. The frequency of CC to TT mutations in aggressive (36%) and nonaggressive SCCs (39%) was 2-fold higher than in aggressive (18%) and nonaggressive (14%) BCCs. In contrast, aggressive BCCs had a higher frequency (24%) of transversions than nonaggressive BCCs (8%) and aggressive (14%) and nonaggressive (11%) SCCs did. CONCLUSIONS: Our results indicate that UV radiation is responsible for the induction of p53 mutations and perhaps for the initiation of both aggressive and nonaggressive BCCs and SCCs. Although some differences in p53 mutation frequency, types of mutation, and hot spots were seen between aggressive and nonaggressive BCCs and SCCs, these factors do not constitute as clear-cut diagnostic or prognostic indicators of tumor aggressiveness. Tumor aggressiveness may be attributable to other genetic changes or events that occur during tumor progression.

Febrile Seizures After 2010-2011 Trivalent Inactivated Influenza Vaccine.

OBJECTIVES: In the Post-Licensure Rapid Immunization Safety Monitoring Program, we examined risk of febrile seizures (FS) after trivalent inactivated influenza vaccine (TIV) and 13-valent pneumococcal conjugate vaccine (PCV13) during the 2010-2011 influenza season, adjusted for concomitant diphtheria tetanus acellular pertussis-containing vaccines (DTaP). Assuming children would receive both vaccines, we examined whether same-day TIV and PCV13 vaccination was associated with greater FS risk when compared with separate-day vaccination. METHODS: We used a self-controlled risk interval design, comparing the FS rate in a risk interval (0-1 days) versus control interval (14-20 days). Vaccinations were identified in claims and immunization registry data. FS were confirmed with medical records. RESULTS: No statistically significant TIV-FS associations were found in unadjusted or adjusted models (incidence rate ratio [IRR] adjusted for age, seasonality, and concomitant PCV13 and DTaP: 1.36, 95% confidence interval [CI] 0.78 to 2.39). Adjusted for age and seasonality, PCV13 was significantly associated with FS (IRR 1.74, 95% CI 1.06 to 2.86), but not when further adjusting for concomitant TIV and DTaP (IRR 1.61, 95% CI 0.91 to 2.82). Same-day TIV and PCV13 vaccination was not associated with excess risk of FS when compared with separate-day vaccination (1.08 fewer FS per 100 000 with same day administration, 95% CI -5.68 to 6.09). CONCLUSIONS: No statistically significant increased risk of FS was found for 2010-2011 TIV or PCV13, when adjusting for concomitant vaccines. Same-day TIV and PCV13 vaccination was not associated with more FS compared with separate-day vaccination.

Primary prevention: why focus on children & young adolescents?

A focus on children and young adolescents in the primary prevention of health risks and disorders such as cancer, hypertension and other cardiovascular diseases, HIV/AIDS, and obesity has been suggested in many reports published throughout the world. Such a focus is important in India as it has a huge adolescents and children population along with the existing economic, social, and health inequalities among the general population. We propose a systematic elucidation of the rationale for such a focus in primary prevention research. We have reviewed studies describing risk factors, the association between risk factors and disease outcomes in affected patients, exposed populations, adolescent samples, as well as reports from studies conducted in India, and the quantitative and qualitative statistical aspects of research. The literature indicates that a lengthy time interval occurs between exposure to high risk factors and the development of disease, and that many such high risk exposures begin in young adolescence. These findings underline the value of targeting children and adolescents for primary prevention efforts in health care and health education for the attainment of overall healthy population in any country including a country like India.

Improving erythropoietin-stimulating agent administration in a multihospital system through quality improvement initiatives: a pre-post comparison study.

INTRODUCTION: : Erythropoietin-stimulating agent (ESA) use is associated with serious adverse events in patients with hemoglobin levels of 12 g/dL or higher at the time of administration. Our aim was to determine whether inappropriate ESA use has changed over time since the implementation of new drug warning alerts and local quality improvement initiatives. MATERIALS AND METHODS: : We performed a retrospective review of ESA administration practices at Memorial Hermann Healthcare System (Houston, Tex). Our primary outcome measure was the proportion of inpatient encounters (one entire inpatient hospital stay) with 1 or more inappropriate uses of ESA (defined as ESA administration for a patient with hemoglobin ≥12 g/dL). We analyzed the potential influence of local and national interventions on ESA utilization patterns. RESULTS: : Between May 1, 2006, and May 31, 2009, 15,642 inpatients were treated with ESAs in our system. We classified inpatients as before intervention (n = 6350) and after intervention (n = 9292) based on the date of implementation of a synchronous alert in the electronic medical record. We found a significant decrease in inappropriate ESA administration before to after intervention (9.03%-6.21%; P < 0.001), which can be translated into a 31.25% (05% CI, 21.93%-40.75%) relative risk reduction. Reduced odds ratios for inappropriate ESA use changed little after controlling for relevant demographic variables and clinical characteristics. CONCLUSIONS: : Following several quality improvement interventions to improve patient safety related to ESA use, we found a significant reduction in inappropriate ESA administration to inpatients in a large health care system.

Ethics of transparency in research reports.

Transparency in research methods and results is now widely seen as an imperative if the healthcare and research enterprise is to be truly successful. A patient-centred focus in the conduct of clinical care includes its safety, effectiveness, efficiency, equity, and timeliness. Innovative ways are being developed to understand, disseminate, and rapidly apply the best evidence to care delivery. In this article, we demonstrate the use of simple and appropriate statistics in research reports that should help healthcare providers apply knowledge to practice by making it easier for them to understand clinical medicine.