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1.
Pharmacoepidemiol Drug Saf ; 25 Suppl 1: 47-55, 2016 Mar.
Article in English | MEDLINE | ID: mdl-26235335

ABSTRACT

PURPOSE: To examine the robustness of findings of case-control studies on the association between acute liver injury (ALI) and antibiotic use in the following different situations: (i) Replication of a protocol in different databases, with different data types, as well as replication in the same database, but performed by a different research team. (ii) Varying algorithms to identify cases, with and without manual case validation. (iii) Different exposure windows for time at risk. METHODS: Five case-control studies in four different databases were performed with a common study protocol as starting point to harmonize study outcome definitions, exposure definitions and statistical analyses. RESULTS: All five studies showed an increased risk of ALI associated with antibiotic use ranging from OR 2.6 (95% CI 1.3-5.4) to 7.7 (95% CI 2.0-29.3). Comparable trends could be observed in the five studies: (i) without manual validation the use of the narrowest definition for ALI showed higher risk estimates, (ii) narrow and broad algorithm definitions followed by manual validation of cases resulted in similar risk estimates, and (iii) the use of a larger window (30 days vs 14 days) to define time at risk led to a decrease in risk estimates. CONCLUSIONS: Reproduction of a study using a predefined protocol in different database settings is feasible, although assumptions had to be made and amendments in the protocol were inevitable. Despite differences, the strength of association was comparable between the studies. In addition, the impact of varying outcome definitions and time windows showed similar trends within the data sources.


Subject(s)
Anti-Bacterial Agents/adverse effects , Chemical and Drug Induced Liver Injury/etiology , Pharmacoepidemiology/standards , Case-Control Studies , Chemical and Drug Induced Liver Injury/epidemiology , Europe/epidemiology , Female , Humans , Male , Middle Aged , Outcome Assessment, Health Care , Pharmacoepidemiology/statistics & numerical data , Risk
2.
Pharmacoepidemiol Drug Saf ; 25 Suppl 1: 21-8, 2016 Mar.
Article in English | MEDLINE | ID: mdl-26147715

ABSTRACT

PURPOSE: The development and validation of algorithms to identify cases of idiopathic acute liver injury (ALI) are essential to facilitate epidemiologic studies on drug-induced liver injury. The aim of this study is to determine the ability of diagnostic codes and laboratory measurements to identify idiopathic ALI cases. METHODS: In this cross-sectional validation study, patients were selected from the hospital-based Utrecht Patient Oriented Database between 2008 and 2010. Patients were identified using (I) algorithms based on ICD-9-CM codes indicative of idiopathic ALI combined with sets of liver enzyme values (ALT > 2× upper limit of normal (ULN); AST > 1ULN + AP > 1ULN + bilirubin > 1ULN; ALT > 3ULN; ALT > 3ULN + bilirubin > 2ULN; ALT > 10ULN) and (II) algorithms based on solely liver enzyme values (ALT > 3ULN + bilirubin > 2ULN; ALT > 10ULN). Hospital medical records were reviewed to confirm final diagnosis. The positive predictive value (PPV) of each algorithm was calculated. RESULTS: A total of 707 cases of ALI were identified. After medical review 194 (27%) patients had confirmed idiopathic ALI. The PPV for (I) algorithms with an ICD-9-CM code as well as abnormal tests ranged from 32% (13/41) to 48% (43/90) with the highest PPV found with ALT > 2ULN. The PPV for (II) algorithms with liver test abnormalities was maximally 26% (150/571). CONCLUSIONS: The algorithm based on ICD-9-CM codes indicative of ALI combined with abnormal liver-related laboratory tests is the most efficient algorithm for identifying idiopathic ALI cases. However, cases were missed using this algorithm, because not all ALI cases had been assigned the relevant diagnostic codes in daily practice.


Subject(s)
Algorithms , Chemical and Drug Induced Liver Injury/diagnosis , Databases, Factual , Hospitals/statistics & numerical data , Humans , International Classification of Diseases/standards , Medical Records
3.
Hum Mol Genet ; 21(17): 3926-39, 2012 Sep 01.
Article in English | MEDLINE | ID: mdl-22532573

ABSTRACT

Recent genome-wide association studies identified 11 single nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk. We investigated these and 62 other SNPs for their prognostic relevance. Confirmed BC risk SNPs rs17468277 (CASP8), rs1982073 (TGFB1), rs2981582 (FGFR2), rs13281615 (8q24), rs3817198 (LSP1), rs889312 (MAP3K1), rs3803662 (TOX3), rs13387042 (2q35), rs4973768 (SLC4A7), rs6504950 (COX11) and rs10941679 (5p12) were genotyped for 25 853 BC patients with the available follow-up; 62 other SNPs, which have been suggested as BC risk SNPs by a GWAS or as candidate SNPs from individual studies, were genotyped for replication purposes in subsets of these patients. Cox proportional hazard models were used to test the association of these SNPs with overall survival (OS) and BC-specific survival (BCS). For the confirmed loci, we performed an accessory analysis of publicly available gene expression data and the prognosis in a different patient group. One of the 11 SNPs, rs3803662 (TOX3) and none of the 62 candidate/GWAS SNPs were associated with OS and/or BCS at P<0.01. The genotypic-specific survival for rs3803662 suggested a recessive mode of action [hazard ratio (HR) of rare homozygous carriers=1.21; 95% CI: 1.09-1.35, P=0.0002 and HR=1.29; 95% CI: 1.12-1.47, P=0.0003 for OS and BCS, respectively]. This association was seen similarly in all analyzed tumor subgroups defined by nodal status, tumor size, grade and estrogen receptor. Breast tumor expression of these genes was not associated with prognosis. With the exception of rs3803662 (TOX3), there was no evidence that any of the SNPs associated with BC susceptibility were associated with the BC survival. Survival may be influenced by a distinct set of germline variants from those influencing susceptibility.


Subject(s)
Breast Neoplasms/diagnosis , Breast Neoplasms/genetics , Genetic Predisposition to Disease , Polymorphism, Single Nucleotide/genetics , Breast Neoplasms/mortality , Databases, Genetic , Female , Gene Expression Regulation, Neoplastic , Genetic Loci/genetics , Genetics, Population , Homozygote , Humans , Middle Aged , Prognosis , Proportional Hazards Models , Receptors, Estrogen/metabolism , Risk Factors
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