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.
METHODS: This study was designed in the form of cross-sectional analysis, in which, cancer survivors were recruited from the Sarawak General Hospital, the largest tertiary and referral public hospital in Sarawak. To capture the financial toxicity of the cancer survivors, the Comprehensive Score for Financial Toxicity (COST) instrument in its validated form was adopted. Multivariable logistic regression analysis was applied to determine the relationship between financial toxicity (FT) and its predictors.
RESULTS: The median age of the 461 cancer survivors was 56 while the median score of COST was 22.0. Besides, finding from multivariable logistic regression revealed that low income households (OR: 6.893, 95% CI, 3.109-15.281) were susceptible to higher risk of financial toxicity, while elderly survivors above 50 years old reported a lower risk in financial toxicity. Also, survivors with secondary schooling (OR:0.240; 95%CI, 0.110-0.519) and above [College or university (OR: 0.242; 95% CI, 0.090-0.646)] suffer a lower risk of FT.
CONCLUSION: Financial toxicity was found to be associated with survivors age, household income and educational level. In the context of cancer treatment within public health facility, younger survivors, households from B40 group and individual with educational attainment below the first level schooling in the Malaysian system of education are prone to greater financial toxicity. Therefore, it is crucial for healthcare policymakers and clinicians to deliberate the plausible risk of financial toxicity borne by the patient amidst the treatment process.
METHODS: From October 2011 to June 2015, 1,778 asymptomatic women, aged 40-74 years, underwent subsidised mammographic screening. All patients had a clinical breast examination before mammographic screening, and women with mammographic abnormalities were referred to a surgeon. The cancer detection rate and variables associated with a recommendation for adjunct ultrasonography were determined.
RESULTS: The mean age for screening was 50.8 years and seven cancers (0.39%) were detected. The detection rate was 0.64% in women aged 50 years and above, and 0.12% in women below 50 years old. Adjunct ultrasonography was recommended in 30.7% of women, and was significantly associated with age, menopausal status, mammographic density and radiologist's experience. The main reasons cited for recommendation of an adjunct ultrasound was dense breasts and mammographic abnormalities.
DISCUSSION: The cancer detection rate is similar to population-based screening mammography programmes in high-income Asian countries. Unlike population-based screening programmes in Caucasian populations where the adjunct ultrasonography rate is 2-4%, we report that 3 out of 10 women attending screening mammography were recommended for adjunct ultrasonography. This could be because Asian women attending screening are likely premenopausal and hence have denser breasts. Radiologists who reported more than 360 mammograms were more confident in reporting a mammogram as normal without adjunct ultrasonography compared to those who reported less than 180 mammograms.
CONCLUSION: Our subsidised opportunistic mammographic screening programme is able to provide equivalent cancer detection rates but the high recall for adjunct ultrasonography would make screening less cost-effective.
METHODS: We extracted sales volume data for 39 anti-cancer medicines from the IQVIA database. We divided the total quantity sold by the reference defined daily dose to estimate the total number of defined daily doses sold, per country per year, for three types of anti-cancer therapies (traditional chemotherapy, targeted therapy and endocrine therapy). We adjusted these data by the number of new cancer cases in each country for each year.
FINDINGS: We observed an increase in sales across all types of anti-cancer therapies in all countries. The largest number of defined daily doses of traditional chemotherapy per new cancer case was sold in Thailand; however, the largest relative increase per new cancer case occurred in Indonesia (9.48-fold). The largest absolute and relative increases in sales of defined daily doses of targeted therapies per new cancer case occurred in Kazakhstan. Malaysia sold the largest number of adjusted defined daily doses of endocrine therapies in 2017, while China and Indonesia more than doubled their adjusted sales volumes between 2007 and 2017.
CONCLUSION: The use of sales data can fill an important knowledge gap in the use of anti-cancer medicines, particularly during periods of insurance coverage expansion. Combined with other data, sales volume data can help to monitor efforts to improve equitable access to essential medicines.
MATERIALS AND METHODS: This cost evaluation refers to 2011, the year in which the observation was conducted. Direct costs incurred by hospitals including the drug acquisition, materials and time spent for clinical activities from prescribing to dispensing of home medications were evaluated (MYR 1=$0.32 USD). As reported to be significantly different between two regimens (96.1% vs 81.0%; p=0.017), the complete response rate of acute emesis which was defined as a patient successfully treated without any emesis episode within 24 hours after LEC was used as the main indicator for effectiveness.
RESULTS: Antiemetic drug acquisition cost per patient was 40.7 times higher for the granisetron-based regimen than for the standard regimen (MYR 64.3 vs 1.58). When both the costs for materials and clinical activities were included, the total cost per patient was 8.68 times higher for the granisetron-based regimen (MYR 73.5 vs 8.47). Considering the complete response rates, the mean cost per successfully treated patient in granisetron group was 7.31 times higher (MYR 76.5 vs 10.5). The incremental cost-effectiveness ratio (ICER) with granisetron-based regimen, relative to the standard regimen, was MYR 430.7. It was found to be most sensitive to the change of antiemetic effects of granisetron-based regimen.
CONCLUSIONS: While providing a better efficacy in acute emesis control, the low incidence of acute emesis and high ICER makes use of granisetron as primary prophylaxis in LEC controversial.
METHODS: In the first part of the analysis costs attributable to cervical cancer and precancerous lesions were estimated; epidemiologic data were sourced from the WHO GLOBOCAN database and Malaysian national data sources. In the second part, a prevalence-based model was used to estimate the potential annual number of cases of cervical cancer and precancerous lesions that could be prevented and subsequent HPV-related treatment costs averted with the bivalent (HPV 16/18) and the quadrivalent (HPV 16/18/6/11) vaccines, at the population level, at steady state. A vaccine efficacy of 98% was assumed against HPV types included in both vaccines. Effectiveness against other oncogenic HPV types was based on the latest results from each vaccine's respective clinical trials.
RESULTS: In Malaysia there are an estimated 4,696 prevalent cases of cervical cancer annually and 1,372 prevalent cases of precancerous lesions, which are associated with a total direct cost of RM 39.2 million with a further RM 12.4 million in indirect costs owing to lost productivity. At steady state, vaccination with the bivalent vaccine was estimated to prevent 4,199 cervical cancer cases per year versus 3,804 cases for the quadrivalent vaccine. Vaccination with the quadrivalent vaccine was projected to prevent 1,721 cases of genital warts annually, whereas the annual number of cases remained unchanged with the bivalent vaccine. Furthermore, vaccination with the bivalent vaccine was estimated to avert RM 45.4 million in annual HPV-related treatment costs (direct+indirect) compared with RM 42.9 million for the quadrivalent vaccine.
CONCLUSION: This analysis showed that vaccination against HPV 16/18 can reduce the clinical and economic burden of cervical cancer and precancerous lesions in Malaysia. The greatest potential economic benefit was observed using the bivalent vaccine in preference to the quadrivalent vaccine.
METHODS: A Markov cohort model reflecting the natural history of HPV infection accounting for oncogenic and low-risk HPV was adapted for 13 year old Malaysian girls cohort (n = 274,050). Transition probabilities, utilities values, epidemiological and cost data were sourced from published literature and local data. Vaccine effectiveness was based on overall efficacy reported from 3-doses clinical trials, with the assumption that the 2-doses is non-inferior to the 3-doses allowing overall efficacy to be inferred from the 3-doses immunogenicity data. Price parity and life-long protection were assumed. The payer perspective was adopted, with appropriate discounting for costs (3 %) and outcomes (3 %). One way sensitivity analysis was conducted. The sensitivity analysis on cost of vaccine, vaccine coverage and discount rate with a 2-doses protocol was performed.
RESULT: The 3-doses and 2-doses regimes showed same number of Cervical Cancers averted (361 cases); QALYs saved at 7,732,266. However, the lifetime protection under the 2-doses regime, showed a significant cost-savings of RM 36, 722,700 compared to the 3-doses scheme. The MOH Malaysia could vaccinate 137,025 more girls in this country using saving 2-doses regime vaccination programme. The model predicted that 2-doses HPV vaccination schemes can avoid additional 180 Cervical Cancers and 63 deaths compare to 3-doses.
CONCLUSION: A 2-doses HPV vaccination scheme may enable Malaysian women to be protected at a lower cost than that achievable under a 3-doses scheme, while avoiding the same number of Cervical Cancer cases and deaths. Using the saving money with 2-doses, more Cervical Cancers and deaths can be avoided.
OBJECTIVES: To evaluate the economic burden of treating cancer patients.
METHOD: Descriptive cross-sectional cost of illness study in the leading teaching and referral hospital in Kenya, with data collected from the hospital files of sampled adult patients for treatment during 2016.
RESULTS: In total, 412 patient files were reviewed, of which 63.4% (n = 261) were female and 36.6% (n = 151) male. The cost of cancer care is highly dependent on the modality. Most reviewed patients had surgery, chemotherapy and palliative care. The cost of cancer therapy varied with the type of cancer. Patients on chemotherapy alone cost an average of KES 138,207 (USD 1364.3); while those treated with surgery cost an average of KES 128,207 (1265.6), and those on radiotherapy KES 119,036 (1175.1). Some patients had a combination of all three, costing, on average, KES 333,462 (3291.8) per patient during the year.
CONCLUSION: The cost of cancer treatment in Kenya depends on the type of cancer, the modality, cost of medicines and the type of inpatient admission. The greatest contributors are currently the cost of medicines and inpatient admissions. This pilot study can inform future initiatives among the government as well as private and public insurance companies to increase available resources, and better allocate available resources, to more effectively treat patients with cancer in Kenya. The authors will be monitoring developments and conducting further research.
METHODS: Through the Association of Southeast Asian Nations Costs in Oncology study, 1,294 newly diagnosed patients with cancer (Ministry of Health [MOH] hospitals [n = 577], a public university hospital [n = 642], private hospitals [n = 75]) were observed in Malaysia. Cost diaries and questionnaires were used to measure incidence of financial toxicity, encompassing financial catastrophe (FC; out-of-pocket costs ≥ 30% of annual household income), medical impoverishment (decrease in household income from above the national poverty line to below that line after subtraction of cancer-related costs), and economic hardship (inability to make necessary household payments). Predictors of financial toxicity were determined using multivariable analyses.
RESULTS: One fifth of patients had private health insurance. Incidence of FC at 1 year was 51% (MOH hospitals, 33%; public university hospital, 65%; private hospitals, 72%). Thirty-three percent of households were impoverished at 1 year. Economic hardship was reported by 47% of families. Risk of FC attributed to conventional medical care alone was 18% (MOH hospitals, 5%; public university hospital, 24%; private hospitals, 67%). Inclusion of expenditures on nonmedical goods and services inflated the risk of financial toxicity in public hospitals. Low-income status, type of hospital, and lack of health insurance were strong predictors of FC.
CONCLUSION: Patients with cancer may not be fully protected against financial hardships, even in settings with universal health coverage. Nonmedical costs also contribute as important drivers of financial toxicity in these settings.