Methods: We performed a literature search to determine preference-based value algorithms in the general population of a given country. We then fitted a second-order quadratic function to assess the utility function curve that links health status with health-care utilities. We ranked the countries according to the concavity and convexity properties of their utility functions and compared this ranking with that of the Hofstede index to check if there were any similarities.
Results: We identified 10 countries with an EQ-5D-5L-based value set and 7 countries with an EQ-5D-3L-based value set. Japan's degree of concavity was highest, while Germany's was lowest, based on the EQ-5D-3L and EQ-5D-5L value sets. Japan also ranked first in the Hofstede long-term orientation index, and rankings related to the degree of concavity, indicating a low time preference rate.
Conclusions: This is the first evaluation to identify and report an association between different cultural beliefs and utility values. These findings underline the necessity to take local values into consideration when designing health technology assessment systems.
METHODS: We performed systematic searches using electronic databases including PubMed and EMBASE until December 2012. Key words included "metformin" AND ("ovarian cancer" OR "ovary tumor"). All human studies assessing the effects of metformin on ovarian cancer were eligible for inclusion. All articles were reviewed independently by 2 authors with a standardized approach for the purpose of study, study design, patient characteristics, exposure, and outcomes. The data were pooled using a random-effects model.
RESULTS: Of 190 studies retrieved, only 3 observational studies and 1 report of 2 randomized controlled trials were included. Among those studies, 2 reported the effects of metformin on survival outcomes of ovarian cancer, whereas the other 2 reported the effects of metformin on ovarian cancer prevention. The findings of studies reporting the effects on survival outcomes indicated that metformin may prolong overall, disease-specific, and progression-free survival in ovarian cancer patients. The results of studies reporting the effects of metformin on ovarian cancer prevention were meta-analyzed. It indicated that metformin tended to decrease occurrence of ovarian cancer among diabetic patients with the pooled odds ratio of 0.57 (95% confidence interval, 0.16-1.99).
CONCLUSIONS: Our findings showed the potential therapeutic effects of metformin on survival outcomes of ovarian cancer and ovarian cancer prevention. However, most of the evidence was observational studies. There is a call for further well-conducted controlled clinical trials to confirm the effects of metformin on ovarian cancer survival and ovarian cancer prevention.
METHODS: We selected two medicines on the 2013 Thai national list of essential medicines (NLEM) [letrozole and imatinib] and three unlisted medicines for the same indications [trastuzumab, nilotinib and dasatinib]. We created timelines of access policies and programs for these products based on scientific and grey literature. Using IMS Health sales data, we described the trajectories of sales volumes of the study medicines between January 2001 and December 2012. We compared estimated average numbers of patients treated before and after the implementation of policies and programs for each product.
RESULTS: Different stakeholders implemented multiple interventions to increase access to the study medicines for different patient populations. During 2007-2009, the Thai Government created a special NLEM category with different coverage requirements for payers and issued compulsory licenses; payers negotiated prices with manufacturers and engaged in pooled procurement; pharmaceutical companies expanded patient assistance programs and lowered prices in different ways. Compared to before the interventions, estimated numbers of patients treated with each medicine increased significantly afterwards: for letrozole from 645 (95% CI 366-923) to 3683 (95% CI 2,748-4,618); for imatinib from 103 (95% CI 72-174) to 350 (95% CI 307-398); and for trastuzumab from 68 (95% CI 45-118) to 412 (95% CI 344-563).
CONCLUSIONS: Government, payers, and manufacturers implemented multi-pronged approaches to facilitate access to targeted cancer therapies for the Thai population, which differed by medicine. Routine monitoring is needed to assess clinical and economic impacts of these strategies in the health system.