Adverse event analysis

Mould, D.R., Holford, N.H.G., Schellens, J.H.M., Beijen, J.H., Hutson, P.R., Rosing, H., ten Bokkel Huinink, W.W., Rowinsky, E., Schiller, J.H., Russo, M., and Ross, G. Population pharmacokinetic and adverse event analysis of topotecan in patients with solid tumors. Clinical Pharmacology and Therapeutics 2002 71 334-348. 

Gortzalez-Formoso, C., Martin-Miguel, M.V., Femandez-Dominguez, M.J., Rial, A., Lago-Deibe, F.I., Ramil-Hermida, L., Perez-Garcia, M. and Claveria, A. 2011. Adverse events analysis as an educational tool to improve patient safety crrltrrre in primary care A randomized trial. BMC Family Practice, 12, 50. 

Adverse event analysis is conducted by those knowledgeable in human factor design principles (e.g., hindsight bias). 

Bhananker SM, O Donnell JT, Salem JR, Bishop 25 MJ The risk of anaphylactic reactions to rocuro-nium in the United States is comparable to that of vecuronium an analysis of food and drug administration reporting of adverse events. Anesth Analg 26 2005 101 819. 

Expert opinion is a source, frequently elicited by survey, that is used to obtain information where no or few data are available. For example, in our experience with a multicountry evaluation of health care resource utilization in atrial fibrillation, very few country-specific published data were available on this subject. Thus the decision-analytic model was supplemented with data from a physician expert panel survey to determine initial management approach (rate control vs. cardioversion) first-, second-, and third-line agents doses and durations of therapy type and frequency of studies that would be performed to initiate and monitor therapy type and frequency of adverse events, by body system and the resources used to manage them place of treatment and adverse consequences of lack of atrial fibrillation control and cost of these consequences, for example, stroke, congestive heart failure. This method may also be used in testing the robustness of the analysis [30]. 

Current computerized analyses of adverse events still typically consist of a vast number of discrete, often personal, ad hoc processes that mimic paper and pencil methods. Some commercial-off-the-shelf (COTS) software tools (e.g., Adobe Acrobat , Microsoft Word , Excel ) do have the capability to search for specihc terms in electronic documents/case reports and do have navigational tools with hyperlinks and fullfull-text indexing that enable researchers to create their own hyperlinks. Some other COTS software tools (e.g., SAS , Excel , Access , IMP ) allow importation of electronic case report tabulations (ECRT) for more detailed analysis. 

It is therefore easy to see why this current drug safety paradigm, with its lack of standards in data collection and analysis, hinders the analysis of adverse events. Without data standards in place, it is difficult to build practical, reusable tools for systematic safety analysis. With no standard tools, truly standardized analyses cannot occur. Reviewers may forget their initial analytical processes if they are not using standardized data and tools. Comprehensive reproducibility and auditability, therefore, become nearly impossible. In practice, the same data sets and analytical processes cannot be easily reused, even by the same reviewers who produced the original data sets and analyses. Not using standardized tools slows the real-time systematic analysis... 

Adverse events need to be coded consistently with respect to letter case. Problems can occur when there is discordant coding using all capital letters, all lower-case letters, or combinations thereof, as computer software will interpret these capitalization variations as different events. Letter case sensitivity can be important when two or more words are used to describe an adverse event. For example, some databases utilizing the Medical Dictionary for Regulatory Activities (MedDRA) coding dictionary employ a coding system in which only the first letter of the first word of an adverse event is capitalized (e.g., Atrioventricular block complete ). Failing to adhere to uniform letter case conventions across the data can result in severe errors in data analysis. 

There is only one good solution to handling free-text variables that are needed for statistical analysis. The free-text variables need to be coded by clinical data management in the clinical database. If the adverse events were coded with a dictionary such as MedDRA, the previous example might look like Program 2.3. 

The study termination form data may be used for efficacy or safety analysis purposes. With regard to safety, if patients discontinue a study medication earlier than patients on standard therapy or placebo, then that is important to know. For efficacy analyses, patients who withdraw due to a lack of efficacy or adverse event may be precluded from being considered a treatment responder or success. Also, often the study termination date is used as a censor date in time-to-event analyses for therapy efficacy. Study termination forms play a key role in patient disposition summaries found at the start of a clinical study report. From a CDISC perspective, the study termination form is a finding. 

Time is a critical measure for clinical trial analysis. Time is captured in clinical trial databases in a study day variable. Study day can be defined as the number of days from therapeutic intervention to any given time point or event. By defining study day, you create a common metric for measuring time across a population of patients in a clinical trial. There can be a study day calculation for any time point of interest. Adverse event start, study termination, and clinical endpoint event date all make good choices for study day calculations. The study day calculation is performed with one of the two following approaches. 

Medical dictionaries often need to be referenced when creating various analysis data sets For instance, perhaps the raw adverse event database in your clinical data management system contains only the MedDRA code. The code is worth having, but you would need the adverse event body system and preferred medical term to provide a useful summary of events. 

The analysis of safety data may require larger data sets, so care in ensuring that a consistent phenotype is collected will be important. Furthermore, the benefit to the drug development program could be that additional data to predict adverse events could be available at the time a drug is marketed. 

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