A Pharmacovigilance Approach for Assessing Cardiovascular, Osteological, and Carcinogenic Risk Associated with Thiazolidinedione Drugs Used in the Treatment of Type 2 Diabetes Mellitus
Bibliographic record
Abstract
Diabetes is a chronic and debilitating disease that affects nearly half a billion people worldwide with the vast majority of diabetics suffering from Type 2 diabetes mellitus (T2DM), a disease characterized by insulin insensitivity that often requires pharmacotherapy to effectively maintain target blood sugar levels. The thiazolidinedione (TZD) class of drugs consists of oral hypoglycaemic agents used alone or in combination with other antidiabetic drugs to treat T2DM. The drugs within this class, which include rosiglitazone and pioglitazone, were originally heralded as providing novel first and second-line treatment of T2DM with glycaemic control and physiological effects comparable to, and in some cases, better than, first-line treatments such as metformin. However, over time they have also been associated with adverse cardiovascular, osteological, and carcinogenic effects in some, but not all clinical trials, observational studies, and meta-analyses. Given the conflicting evidence to date on the safety of TZD drugs, their role in the treatment of T2DM continues to be debated and epidemiological gaps remain. The objectives of this doctoral research are fourfold: 1) to conduct an in-depth review of the epidemiology of TZD pharmacotherapy including pharmacokinetics and modes of action, the results of previous studies investigating health risks and benefits associated with TZD treatment, and new and future uses for this class of drugs; 2) to determine whether diabetic patients treated with TZDs are at increased risk of adverse cardiovascular outcomes; 3) to assess whether TZD pharmacotherapy is associated with an increased risk of bone fractures and whether risks differ depending on fracture site and patient sex; and, 4) to investigate associations between TZD use and risk of bladder cancer. Specific research questions were investigated using nested case-control analyses designed to capture incident users of antidiabetic drugs and electronic health data from Cerner Health Facts®, an electronic medical record database that stores time-stamped patient records from more than 480 contributing hospitals throughout the United States. Findings from this work are reported in a series of manuscripts, including a published review paper. Key findings include: 1) TZD use was associated with an increased risk of incident myocardial infarction and congestive heart failure compared to never use of TZD drugs with a trend towards a potential early treatment effect within the first year of exposure to pioglitazone; 2) TZD use was associated with an increased risk of closed bone fractures among Type 2 diabetics with use of pioglitazone or rosiglitazone associated with an increased risk across multiple fracture sites in women, but only rosiglitazone use in men and only at peripheral fracture sites; 3) use of either pioglitazone or rosiglitazone were associated with an increased risk of incident bladder cancer compared to never users, however, a low number of bladder cancer cases resulted in underpowered analyses; and, 4) insulin use in a hospital setting may replace a patient's normal course of antidiabetic therapy which, when combined with other potential sources of bias in traditional nested case-control studies using hospital-based data, may lead to overestimation or underestimation of adverse health risks associated with non-insulin antidiabetic therapies. Although these findings warrant replication, the results of the research contained within this dissertation suggest that caution should be exercised when prescribing diabetic patients TZD drugs if they have cardiovascular, osteological, or carcinogenic risk factors. Additional pharmacovigilance studies should also continue to strive to better understand the health risks related to TZD therapy, especially as new therapeutic roles for TZDs in the prevention and treatment of some cancers, inflammatory diseases, and other conditions in non-diabetic populations are being explored.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.011 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".