Journal of acquired immune deficiency syndromes and human retrovirology : official publication of the International Retrovirology Association
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J. Acquir. Immune Defic. Syndr. Hum. Retrovirol. · May 1996
Off-label drug use in human immunodeficiency virus disease.
We wished to determine the extent to which drugs used to treat HIV disease and its clinical manifestations are prescribed for conditions other than those listed on the U. S. Food and Drug Administration's approved drug label, how such "off-label" use varies by patient characteristics and type of HIV-related medical condition, and the extent to which physicians alter the way they treat HIV-related conditions because of reimbursement problems associated with off-label drug use. ⋯ The use of drugs for off-label indications in HIV care is common and frequently represents community standards of care. Reliance on drug compendia for support of off-label drug use accounts for the majority of such uses, although many legitimate off-label uses may not be included because of compendia publication lag. The prevalence of off-label drug use in routine clinical practice and the development of newer and more costly drugs for treatment of HIV and its medical complications argues for the articulation of an explicit national reimbursement policy for off-label uses of prescription drugs so that medically appropriate therapies will be available to those with insurance in a rational, consistent way.
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J. Acquir. Immune Defic. Syndr. Hum. Retrovirol. · May 1996
Comparative Study Clinical Trial Controlled Clinical TrialImpact of missing data due to dropouts on estimates of the treatment effect in a randomized trial of antiretroviral therapy for HIV-infected individuals. Canadian HIV Trials Network A002 Study Group.
To evaluate the impact of missing data due to nonrandom dropout on estimates of the effect of treatment on the CD4 count in a clinical trial of antiretroviral therapy for HIV infected individuals. ⋯ Missing outcome data due to dropouts can result in an underestimation of the treatment effect and overly optimistic statements about the outcome of participants on both treatment arms due to the selective dropout of participants with lower or decreasing CD4 counts. When there are significant dropout rates in randomized trials, imputation is a useful technique to assess the range of plausible values of the treatment effect.