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close this bookCost-Effectiveness Tool for Evaluating Interventions to Prevent Mother-to-Child Transmission - Manual and Model (UNAIDS, 2000, 94 p.)
close this folder“ARV” WORKSHEET
View the document(introduction...)
View the documentTABLE ARV-1: REGIMEN COMPONENTS
View the documentTABLE ARV-2: GESTATIONAL AGE AT START OF TREATMENT
View the documentTABLE ARV-3: MOTHERS AND CHILDREN RECEIVING VARIOUS SERVICE COMPONENTS
View the documentTABLE ARV-4: DOSES, DRUGS AND DRUG COSTS.
View the documentTABLE ARV-5: EFFECTIVENESS ESTIMATES
View the documentTABLE ARV-6: ARV EFFECTIVENESS - ADJUSTMENTS FOR IMPERFECT ADHERENCE

TABLE ARV-6: ARV EFFECTIVENESS - ADJUSTMENTS FOR IMPERFECT ADHERENCE

Background

“Imperfect adherence” refers to the difference between the intended number and timing of doses in a regimen and the number and timing actually experienced by patients. The efficacy estimates incorporated into this model are based on the results of well-funded clinical trials. It is possible that patient adherence outside the trial setting will be lower than in the trials. The actual efficacy experienced in your client population may therefore also differ once adherence rates are taken into account. While lower adherence is undoubtedly associated with lower efficacy in general, the specific relation between the two have not been documented for the regimens under analysis. The default value of adjustments to reflect imperfect adherence is 0%. This means that adherence is expected to be the same as was attained in the trials. Depending on the setting, this may not be realistic. For example the infrastructure present in the industrialized countries where ACTG 076 was conducted may not be available in lower income countries. Adherence to this regimen may therefore be lower.

Treatment Adherence Rates

Country

Rates

Source

Northern Thailand

90% adherence

Thaineua et al., 1998

NTPHPT (Thailand)

99% of the women took at least 90% of the antenatal ZDV doses and 99% took at least 1 dose during labor

Weekly Epidemiological Record, 1998

UNAIDS PETRA trials (Uganda, Tanzania, South Africa)

7.7% of women did not take any of the prescribed medication

Marseille et al., 1998

Source: Adapted from John Stover, TFGI, 1999.

As shown in the table above, adherence can be variable even in the context of well funded clinical trials. The very sparse data that is available suggest that adherence may be more of a problem in sub-Saharan Africa than in Thailand. It is also possible that adherence will increase as people understand that they are taking a proven effective drug rather than a possible placebo or a drug which may or may not be effective. The adherence adjustment cells (ARVs-C98 - G98) can accept negative values. This would indicate that adherence in your project is better than that experienced in the trials and that this greater a adherence is associated with greater efficacy.

Unless good adherence data is available from your project we suggest you retain the default value of 0%. This makes for consistent comparisons with results generated by other users of this model. However, if you have reason to believe that adherence may be significantly above or below the levels experienced in the trials, cells C98 through G98 allow one to explore the consequences of different assumptions about adherence and its bearing on effectiveness.

Influence on cost-effectiveness: Potentially high. Adherence directly affects efficacy.

Expected effort of data collection: High. Since low adherence will render any intervention ineffective, most projects will find it worthwhile to monitor adherence independent of a cost-effectiveness analysis.

C98 - G98. Imperfect adherence. After reading the cautionary notes in the preceding paragraphs, enter changes in the adjustment for efficacy to reflect imperfect adherence if you believe they are warranted. Data sources: Project patient records.