Health care utilization data

Although the intervention showed no statistically significant effect of acupressure over sham acupressure and no acupressure, the health economics part of the trial run concurrently with the effectiveness part of the trial. Also, through health economics analyses in negative trials it is possible intervention benefits that are not apparent in traditional efficacy endpoints may register in QALYs, as this is a different, composite outcome. Current thinking in respect of economic analyses in cases where there is no clear differential effect/effectiveness in the intervention being assessed is that a full cost effectiveness analysis is undertaken and uncertainty accounted for. Even given that the EQ-5D changes were below minimally important and not significant, and the QALY gains were minimal (for acupressure vs standard care) one cannot evaluate the cost- effectiveness without considering costs81,82_.

Mean costs resulting from NHS resource use were consistently higher for the standard care only group compared to the acupressure group; this finding was relatively robust to sensitivity analyses. However, since very little resource use was recorded in the study and results may have been unduly influenced by outliers with high costs, this finding is relatively uncertain and must be treated with caution. Results from the EQ-5D score analysis revealed no significant differences in utility changes over time between treatment arms and QALY gains throughout the study were negligible.

The acupressure bands group appears to have reduced health care resource use whilst realising negligible improvements in quality of life compared to standard care alone. A rapid review of the literature found no studies including costs of chemotherapy-induced nausea and vomiting to the NHS, precluding comparison with previous research. Neither did the review yield any previous studies reporting EQ-5D scores for this patient group. In the present study the EQ-5D showed no differences in utility between groups. There also appeared little overall impact of chemotherapy as no utility score changes between any cycle exceeded (or came close to exceeding) the minimal important difference identified for the measure. EQ-5D scores were similar to population norms78 at the final chemotherapy cycle for the older patients but the younger patients appeared to experience a greater utility decrement relative to norms. The mean utility for both the 25-50 and ≥ 50 age groups was 0.77 after cycle four, compared to population norms of 0.90 for the 25-54 age group and 0.79 for the 55-74 age group. It is possible that the EQ-5D is not sensitive enough a measure to capture quality of life benefits that may be experienced as a result of reduced chemotherapy-induced nausea and vomiting although a cancer-specific quality of life measure

(FACT-G) also failed to detect any between group differences. There is also a non-significant baseline difference in utility scores between groups which may explain differential QALY gains over the trial period.

There were several limitations in this economic evaluation. We made assumptions regarding drug doses and anti-emetics drug type due to missing data and also made assumptions regarding length of hospital stay. Assumptions were also necessary regarding the standard care of each of the patients, relying on expert opinion and assuming care was the same across centres. It is possible that more expensive (branded) anti-emetic treatments may have been used but not captured as not all prescribing information was available. Different sites may have different protocols relating to anti-emetic prescription as a standard therapy. However, the incremental cost effectiveness ratios and the resulting conclusions regarding the cost-effectiveness of acupressure were robust to sensitivity analyses and stochastic bootstrapping.

When calculating the EQ-5D missing data we employed the last observation carried forward (LOCF) approach; this method assumes that the participant's EQ-5D response would have been stable between each cycle, rather than declining or improving. It also assumes that missing values are “missing completely at random” (i.e. that the probability of dropout is not related to variables such as disease severity, symptoms, or drug side effects). As such, the LOCF method may lead to bias in the results. However, assumptions about both costs and utility were tested in the sensitivity analyses. Finally, it is possible that the EQ-5D is an inappropriate measure to capture health benefits incurred as a result of reduced nausea and that a cancer-specific measure may be more suitable79_{. However, cost-utility analyses and the EQ-5D are compliant with the NICE}

reference case. Future research should consider cancer-specific utility measurement and comparisons with generic utility values. As the occurrence and impact of chemotherapy-induced nausea and vomiting varies over time in relation to chemotherapy receipt, quality of life impact depends on the time of measure completion during the cycle. Thus research exploring patients’ health status on a daily basis throughout the course of a chemotherapy cycle may be warranted. Given the influence of high-cost outliers in the analyses, greater exploration of what is driving these costs and indeed whether they relate to chemotherapy-induced nausea and vomiting may be worthwhile; this may involve qualitative follow-up of high-resource use individuals.