Estimating and Rewarding the Value of Healthcare Interventions Beyond the Healthcare Sector: A Conceptual Framework.

BACKGROUND: Evaluating healthcare interventions for their impacts beyond health outcomes may result in recognition of changes in human capital, income level, tax revenue, and government spending, which could affect economic growth and population health. In this paper, we document instances where current health technology assessment (HTA) practices fail to account for the impacts of healthcare interventions on broader society beyond the healthcare sector. METHODS: We propose a novel conceptual framework, highlighting its three components (distributional cost-effectiveness analysis [DCEA], input-output model, and voting scheme) and their contributions to capturing the economic and societal ripple effects of healthcare interventions. This manuscript also outlines a case study in which the framework is applied to the reassessment of a previously evaluated digital health therapeutic for the treatment of opioid use disorder (OUD) compared with standard of care, demonstrating its practical application. RESULTS: The DCEA health value metric indicates that digital therapeutic is more equitable, favoring socioeconomically disadvantaged groups, while standard of care exacerbates health inequality by benefiting the already advantaged. Additionally, digital therapeutic shows potential for boosting productivity, raising income, and creating jobs, supporting its consideration by employer-sponsored health plans to optimize resource allocation for treating OUD. CONCLUSION: The conceptual framework provides insights for enhancing HTAs to incorporate the broader economic and societal impacts of healthcare interventions. By integrating DCEA, extended HTA analysis with input-output modeling, and a voting scheme, decision makers can make informed choices aligned with societal priorities, although further research and validation are necessary for practical implementation across diverse healthcare contexts.

The State of Pharmacoeconomics Education in the Doctor of Pharmacy Curriculum amid the Changing Face of Pharmacy Practice.

(1) Background: Continuous growth in pharmaceutical expenditure indicates the need for more advanced pharmacoeconomics evaluations to optimize healthcare outcomes and resource allocation. This study assesses the extent to which accredited pharmacy colleges in the United States cover pharmacoeconomics content within the didactic curriculum of their Doctor of Pharmacy (PharmD) programs. (2) Methods: We conducted a systematic search of the websites of accredited professional-degree programs in pharmacy schools located in the United States to identify pertinent content related to pharmacoeconomics. (3) Results: Out of 141 pharmacy programs, a total of 111 programs of varying sizes were found to have publicly accessible information regarding the content of their pharmacoeconomic curricula on their websites. All these programs required the inclusion of pharmacoeconomics content in their curricula. An examination of course syllabi revealed that the goals and descriptions were broad, aiming to provide students with an introductory understanding of the principles of pharmacoeconomics. The number of credit hours allocated to pharmacoeconomics education ranged from one to seven across the programs. The approach to delivering pharmacoeconomics content varied among the programs. (4) Conclusions: Advanced knowledge of the principles of pharmacoeconomics must be an integral component of all PharmD curricula to prepare pharmacists to assess the rational use of pharmacy products and services, improve clinical outcomes, and mitigate healthcare expenditures.

Deep Learning-Based Survival Analysis for Receiving a Steatotic Donor Liver Versus Waiting for a Standard Liver.

BACKGROUND: An emerging strategy to expand the donor pool is the use of a steatotic donor liver (SDLs; ≥ 30% macrosteatosis on biopsy). With the obesity epidemic and prevalence of nonalcoholic fatty liver disease, SDLs have been reported in 59% of all deceased donors. Many potential candidates need to decide whether to accept an SDL offer or remain on the waitlist for a nonsteatotic donor liver (non-SDL). The objective of this study was to compare the survival of accepting an SDL vs using a non-SDL after waiting various times. METHODS: Using data from the United States' organ procurement and transplantation network, deep survival learning predictive models were built to compare post-decision survival after accepting an SDL vs waiting for a non-SDL. The comparison subjects contain simulated 20,000 different scenarios of a candidate either accepting an SDL immediately or receiving a non-SDL after waiting various times. The research variables were selected using the LASSO-Cox and Random Survival Forest (RSF) models. The Cox proportional hazards and RSF models were also comparatively included for survival prediction. In addition, personalized survival curves for randomly selected candidates were generated. RESULT: Deep survival learning outperformed Cox proportional hazards and RSF in predicting the survival of liver transplants. Among the simulations, 25% to 30% of scenarios demonstrated a higher 3-year survival post-decision for candidates accepting an SDL than waiting and receiving a non-SDL. The difference was only 1.43% in 3-year survival post-decision between accepting an SDL and waiting 260 days (mean waitlist time) for a non-SDL. As the number of days on the waitlist increases, the difference in survival between accepting SDLs and waiting for non-SDLs decreases. CONCLUSIONS: Appropriately used SDLs could expand the donor pool and relieve the candidates' unmet need for donor livers, which presents long-term survival benefits for recipients.

Development and validation of a tool to predict high-need, high-cost patients hospitalised with ischaemic heart disease.

OBJECTIVE: To develop and validate a tool to predict patients with ischaemic heart disease (IHD) at risk of excessive healthcare resource utilisation. DESIGN: A retrospective cohort study. SETTING: We identified patients through the State of Florida Agency for Health Care Administration (N=586 518) inpatient dataset. PARTICIPANTS: Adult patients (at least 40 years of age) admitted to the hospital with a diagnosis of IHD between 1 January 2007 and 31 December 2016. PRIMARY OUTCOME MEASURES: We identified patients whose healthcare utilisation is higher than presumed (analysis of residuals) and used logistic regression (binary and multinomial) in estimating the predictive models to classify individual as high-need, high-care (HNHC) patients relative to inpatient visits (frequency of hospitalisation), cost and hospital length of stay. Discrimination power, prediction accuracy and model improvement for the binary logistic model were assessed using receiver operating characteristic statistic, the Brier score and the log-likelihood (LL)-based pseudo-R2, respectively. LL-based pseudo-R2 and Brier score were used for multinomial logistic models. RESULTS: The binary logistic model had good discrimination power (c-statistic=0.6496), an accuracy of probabilistic predictions (Brier score) of 0.0621 and an LL-based pseudo-R2 of 0.0338 in the development cohort. The model performed similarly in the validation cohort (c-statistic=0.6480), an accuracy of probabilistic predictions (Brier score) of 0.0620 and an LL-based pseudo-R2 of 0.0380. A user-friendly Excel-based HNHC risk predictive tool was developed and readily available for clinicians and policy decision-makers. CONCLUSIONS: The Excel-based HNHC risk predictive tool can accurately identify at-risk patients for HNHC based on three measures of healthcare expenditures.

Machine learning algorithms to predict major adverse cardiovascular events in patients with diabetes.

BACKGROUND: Major Adverse Cardiovascular Events (MACE) are common complications of type 2 diabetes mellitus (T2DM) that include myocardial infarction (MI), stroke, and heart failure (HF). The objective of the current study was to predict MACE among T2DM patients. METHODS: Type 2 diabetes mellitus patients above 18 years old were recruited for the study from the All of Us Research Program. Eligible participants were those who took sodium-glucose cotransporter 2 inhibitors. Different Machine learning algorithms: including RandomForest (RF), XGBoost, logistic regression (LR), and weighted ensemble model (WEM) were employed. Clinical attributes, electrolytes and biomarkers were explored in predicting MACE. The feature importance was determined using mean decrease accuracy. RESULTS: Overall, 9, 059 subjects were included in the analyses, of which 5197 (57.4%) were females. The XGBoost Model demonstrated a prediction accuracy of 0.80 [0.78-0.82], which is higher as compared to the RF 0.78[0.76-0.80], the LR model 0.65 [0.62-0.67], and the WEM 0.75 [0.73-0.76], respectively. The classification accuracy of the models for stroke was more than 95%, which was higher than prediction accuracy for MI (∼85%), and HF (∼80%). Phosphate, blood urea nitrogen and troponin levels were the major predictors of MACE. CONCLUSION: The ML models had shown acceptable performance in predicting MACE in T2DM patients, except the LR model. Phosphate, blood urea nitrogen, and other electrolytes were important predictors of MACE, which is consistent between the individual components of MACE, such as stroke, MI, and HF. These parameters can be calibrated as prognostic parameters of MACE events in T2DM patients.

Association of Preventive Care Attitudes and Beliefs with Colorectal Cancer Screening History among African American Patients of Community Health Centers.

Colorectal cancer (CRC) is the third most common cancer and third leading cause of cancer-related death among African Americans in the United States. However, when detected early, CRC is treatable and survival rates are high. CRC health disparities for African Americans compared with other groups may be due in part to lower screening adherence and later stage diagnosis. The objective of this research phase was to test predictors of ever having received CRC screening (i.e., self-report of lifetime receipt of CRC screening) using survey measures in the domains of healthcare communication, trust in doctors, CRC perceived susceptibility, CRC worry, negative cancer beliefs, CRC screening self-efficacy, and cultural constructs for CRC screening in a sample of African American community health center patients. The study recruited 115 African American patients between the ages of 45 to 64 years old from community health centers in north Florida to complete the baseline survey. Our results show significant differences in CRC screening history by age, marital status, level of mistrust of healthcare providers, and level of empowerment toward cancer screening. To increase CRC screening in this population, the study findings suggest development of intervention programs that focus on priority populations of younger, unmarried African Americans, especially given the current trend of early onset CRC. Moreover, survival rates are lower for unmarried and younger African Americans relative to older and married individuals. Such interventions should also aim to increase trust in healthcare providers and increase empowerment for CRC screening decision making to increase screening participation.

Statins utilization trends and expenditures in the U.S. before and after the implementation of the 2013 ACC/AHA guidelines.

Importance: Statins are drugs of choice in treating hyperlipidemia and preventing or reducing cardiovascular diseases. Purpose: Explore statins utilization and expenditure trends in the United States before and after the publication of the 2013 ACC/AHA guidelines. Method: A retrospective, cross-sectional study of US noninstitutionalized civilians was conducted using MEPS data from 2008 to 2019. Adults who were ≥ 40 years old and who reported taking statins were included in the study. Primary outcomes: Statins use patterns, total cost, and out-of-pocket spending in the general adults who reported taking statins medications. Expenditures were expressed in 2019 US dollars. Results: In this study, 409,804 individuals were eligible to be included (mean age [SE], 59 [0.1] years; 54% female). Of those participants, 22% reported taking statin therapy, and 11% of them filled only one statin prescription. The number of individuals in the general population who reported taking any statin climbed from 31 million (12%) in 2008-2009 to 92 million (35%) in 2018-2019, representing a 197% increase. After 2013, the number of individuals who used statins increased by 149%, from 37 million in 2012-2013 to 92 million users in 2018-2019. The annual number of statins prescriptions increased from 461 million to 818 million (77%; p = 0.000) between 2008 and 2019. Atorvastatin was the most prescribed medication in the statins class (36%), followed by simvastatin (34%). The moderate-intensity statins were the most used by the participants (60%). The total statins cost in 2013 was $8 billion and increased to $10 billion in 2019 (25%; p = 0.000). The total OOP expenditure trend sloped from $4.0 billion in the 2008-2009 cycle to $3.1 billion in 2018-2019. The average OOP paid by Asians was higher than that of other races at $141. Conclusion: The proportion of individuals who used statins significantly increased following the adoption of the 2013 ACC/AHA guidelines. The findings, however, demonstrated suboptimal prescribing trends of high-intensity statins, which need to be addressed by the stakeholders to maximize medication outcomes. Statins expenditures, especially the co-payments, significantly decreased. The results have shown that revised or new regulations have a substantial impact on the healthcare industry.

Application of Machine Learning Algorithms to Predict Uncontrolled Diabetes Using the All of Us Research Program Data.

There is a paucity of predictive models for uncontrolled diabetes mellitus. The present study applied different machine learning algorithms on multiple patient characteristics to predict uncontrolled diabetes. Patients with diabetes above the age of 18 from the All of Us Research Program were included. Random forest, extreme gradient boost, logistic regression, and weighted ensemble model algorithms were employed. Patients who had a record of uncontrolled diabetes based on the international classification of diseases code were identified as cases. A set of features including basic demographic, biomarkers and hematological indices were included in the model. The random forest model demonstrated high performance in predicting uncontrolled diabetes, yielding an accuracy of 0.80 (95% CI: 0.79-0.81) as compared to the extreme gradient boost 0.74 (95% CI: 0.73-0.75), the logistic regression 0.64 (95% CI: 0.63-0.65) and the weighted ensemble model 0.77 (95% CI: 0.76-0.79). The maximum area under the receiver characteristics curve value was 0.77 (random forest model), while the minimum value was 0.7 (logistic regression model). Potassium levels, body weight, aspartate aminotransferase, height, and heart rate were important predictors of uncontrolled diabetes. The random forest model demonstrated a high performance in predicting uncontrolled diabetes. Serum electrolytes and physical measurements were important features in predicting uncontrolled diabetes. Machine learning techniques may be used to predict uncontrolled diabetes by incorporating these clinical characteristics.

Impact of Sertraline, Fluoxetine, and Escitalopram on Psychological Distress among United States Adult Outpatients with a Major Depressive Disorder.

How impactful is the use of Sertraline, Fluoxetine, and Escitalopram monotherapy on psychological distress among adults with depression in the real world? Selective serotonin reuptake inhibitors (SSRIs) are the most commonly prescribed antidepressants. Medical Expenditure Panel Survey (MEPS) longitudinal data files from 1 January 2012 to 31 December 2019 (panel 17-23) were used to assess the effects of Sertraline, Fluoxetine and Escitalopram on psychological distress among adult outpatients diagnosed with a major depressive disorder. Participants aged 20-80 years without comorbidities, who initiated antidepressants only at rounds 2 and 3 of each panel, were included. The impact of the medicines on psychological distress was assessed using changes in Kessler Index (K6) scores, which were measured only in rounds 2 and 4 of each panel. Multinomial logistic regression was conducted using the changes in the K6 scores as a dependent variable. A total of 589 participants were included in the study. Overall, 90.79% of the study participants on monotherapy antidepressants reported improved levels of psychological distress. Fluoxetine had the highest improvement rate of 91.87%, followed by Escitalopram (90.38%) and Sertraline (90.27%). The findings on the comparative effectiveness of the three medications were statistically insignificant. Sertraline, Fluoxetine, and Escitalopram were shown to be effective among adult patients suffering from major depressive disorders without comorbid conditions.

Health-Related Quality of Life and Healthcare Events in Patients with Monotherapy of Anti-Diabetes Medications.

This study aimed to examine the difference in health-related quality of life (HRQOL) and diabetes-related healthcare events (HCEs) among adults with diabetes who were on metformin, sulfonylurea, insulin, or thiazolidinedione (TZD) monotherapy. The data were sourced from the Medical Expenditure Panel Survey (MEPS). Diabetes patients ≥18 years old who had a complete record of physical component score and mental component scores in round 2 and round 4 of the survey were included. The primary outcome was HRQOL of diabetes patients as measured by the Medical Outcome Study short-form (SF-12v2TM). Multinomial logistic regression and negative binomial regression were conducted to determine associated factors of HRQOL and HCE, respectively. Overall, 5387 patients were included for analysis. Nearly 60% of patients had unchanged HRQOL after the follow-up, whereas almost 15% to 20% of patients showed improvement in HRQOL. The relative risk of declined mental HRQOL was 1.5 times higher relative to unchanged mental HRQOL in patients who were on sulfonylurea 1.55 [1.1-2.17, p = 0.01] than metformin users. The rate of HCE decreased by a factor of 0.79, [95% CI: 0.63-0.99] in patients with no history of hypertension. Patients on sulfonylurea 1.53 [1.20-1.95, <0.01], insulin 2.00 [1.55-2.70, <0.01], and TZD 1.78 [1.23-2.58, <0.01] had increased risk of HCE compared to patients who were on metformin. In general, antidiabetic medications modestly improved HRQOL in patients with diabetes during the follow-up period. Metformin had a lower rate of HCE as compared to other medications. The selection of anti-diabetes medications should focus on HRQOL in addition to controlling glucose level.

Cost Effectiveness of Dapagliflozin Added to Standard of Care for the Management of Diabetic Nephropathy in the USA.

BACKGROUND: Angiotensin-converting enzyme inhibitors have been used as the standard of care for the treatment of diabetic nephropathy. Recently, dapagliflozin has been shown to reduce diabetic nephropathy when added to the standard of care. OBJECTIVE: The objective of this study was to determine the cost effectiveness of dapagliflozin added to the standard of care in diabetic nephropathy in the United States of America (USA). METHODS: A Markov model was developed to determine the cost-effectiveness outcomes from the Medicare/Medicaid health coverage perspective. Model inputs were derived from the literature. The primary outcomes were total costs, quality-adjusted life-years (QALYs), and the incremental cost-effectiveness ratio. Deterministic and probabilistic sensitivity analyses were performed to determine the robustness of our results. A willingness-to-pay threshold of $100,000 per QALY was applied, which is based on previous studies. RESULTS: Dapagliflozin yielded a lifetime QALY of 2.8. The discounted QALY associated with the standard of care was 2.6. The standard of care was the less costly treatment with a lifetime cost of $106,150.25 as compared with dapagliflozin, which costs $110,689.25. Dapagliflozin demonstrated an incremental cost-effectiveness ratio of $21,141.51 per additional QALY. The most influential parameters of the incremental cost-effectiveness ratio were the adverse drug reaction-related cost of the standard of care and dapagliflozin, the acquisition cost, and the adverse drug reaction-related cost of dapagliflozin. The effects and costs of the interventions were consistent between base-case analyses and the probabilistic model (incremental cost-effectiveness ratio: $19,023.35 [$13,637.8-$27,483.1]). CONCLUSIONS: Dapagliflozin added to the standard of care was cost effective relative to the standard of care alone in the USA for patients with diabetic nephropathy.

Assessing the effectiveness of a community health advisor plus screen to save educational intervention on stool-based testing adherence in an African American safety net clinic population: study protocol for a randomized pragmatic trial.

BACKGROUND: Colorectal cancer (CRC) is the second most deadly cancer affecting US adults and is also one of the most treatable cancers when detected at an earlier clinical stage of disease through screening. CRC health disparities experienced by African Americans are due in part to the later stage of diagnosis, suggesting the importance of improving African Americans' CRC screening participation. The national Screen to Save (S2S) initiative employs a community health educator to deliver CRC screening education which can be tailored for specific populations, and such approaches have increased CRC screening rates in disadvantaged and racial/ethnic minority populations. METHODS/DESIGN: In this trial emphasizing stool-based CRC screening, focus groups informed the development of an adapted S2S video and brochure tailored for African Americans and identified preferred motivational text messages for a multicomponent community health advisor (CHA) intervention. A CHA hired from the community was trained to deliver a 6-week CRC educational intervention consisting of an initial face-to-face meeting followed by 5 weeks of calls and texts. Interested eligible persons are enrolled primarily through recruitment by two partnering community health centers (CHCs) and secondarily through various outreach channels and, after consenting and completing a baseline survey, are randomly assigned to one of two study arms. The CHCs are blinded to study arm assignment. Intervention arm participants receive the brochure and CHA intervention while participants assigned to the control group receive only the brochure. All participants receive a stool-based CRC screening test from their health center, and the primary outcome is the completion of the screening test at 12 months. Secondary objectives are to estimate the effect of the intervention on mediating factors, explore the effect of moderating factors, and perform a cost-effectiveness analysis of the CHA intervention. DISCUSSION: The TUNE-UP study will enhance understanding about CRC screening in African Americans obtaining primary health care through CHCs and is one of the very few studies to examine a CHA intervention in this context. A better understanding of the mechanisms by which the intervention affects patient beliefs and behaviors will help focus future research while the exploratory cost-effectiveness analysis will inform CHCs' decision-making about implementing a CHA program to increase screening and reduce cancer health disparities. TRIAL REGISTRATION: ClinicalTrials.gov NCT04304001 . Registered on March 11, 2020.

Comparative cost-effectiveness of radiotherapy among older women with hormone receptor positive early-stage breast cancer.

OBJECTIVE: The aim was to examine the real-world cost-effectiveness of breast-conserving surgery (BCS) plus hormonal therapy with radiotherapy, compared to hormonal therapy alone among women 66 and older with hormone receptor positive early-stage breast cancer in the United States (US). METHODS: This study was conducted from a U.S. Centers for Medicare and Medicaid Services perspective and an eight-year time horizon. Both costs (2020 US$) and health utilities (quality-adjusted life years, QALYs) were obtained from retrospective studies using the SEER linked with Medicare and Medicare Health Outcomes Survey, respectively. The incremental cost-effectiveness ratio (ICER) of the addition of radiotherapy to hormonal therapy versus hormonal therapy alone after BCS was estimated by an unbiased doubly robust estimator. Sensitivity analyses were conducted through bootstrapping to estimate credible intervals. RESULTS: The addition of radiotherapy to hormonal therapy after BCS yielded the highest clinical benefits (2.66 QALYs) and costs ($19,424.27) compared to its hormonal therapy alone after BCS (0.77 QALYS; $2,028.58). The ICER was estimated to be $9,174.94/QALY. Sensitivity analyses did not change the direction of the findings. CONCLUSIONS: The results implicated that the combination of radiotherapy and hormonal therapy is cost-effective in the US.

Engaging the Community on Colorectal Cancer Screening Education: Focus Group Discussions Among African Americans.

Colorectal cancer (CRC) is the third most diagnosed cancer in the USA, and African Americans experience disproportionate CRC diagnosis and mortality. Early detection could reduce CRC incidence and mortality, and reduce CRC health disparities, which may be due in part to lower screening adherence and later stage diagnosis among African Americans compared to whites. Culturally tailored interventions to increase access to and uptake of CRC stool-based tests are one effective strategy to increase benefits of screening among African Americans. The objectives of this study were to obtain feedback from African Americans on CRC educational materials being developed for a subsequent behavioral clinical trial and explore participants' knowledge, attitudes, and beliefs about CRC and CRC screening. Seven focus groups were conducted between February and November 2020. Participants were African Americans recruited through community contacts. Four focus groups were held in-person and three were conducted virtually due to Covid-19 restrictions. Participants ranked CRC educational text messages and provided feedback on a culturally tailored educational brochure. A focus group guide with scripted probes was used to elicit discussion and transcripts were analyzed using traditional content analysis. Forty-two African Americans participated. Four themes were identified from focus group discussions: (1) knowledge, attitudes, and beliefs on CRC and CRC screening; (2) reliable sources of cancer education information; (3) cultural factors affecting perspectives on health; and (4) community insights into cancer education. Participant input on the brochure was incorporated in content creation. Engaging African American community members to qualitatively examine cancer prevention has value in improving implementation strategy and planning for behavioral clinical trials.

Exploratory Analysis of Survival and Mortality Rates among Older Lung Cancer Patients Utilizing Different Treatment Modalities.

Objective: To explore the impact of different lung cancer treatment modalities on survival time and mortality rates in older patients. Methods: The Surveillance Epidemiology and End Results (SEER) database was used to identify lung cancer patients aged ≥50 years old in the United States. Descriptive statistics and trend charts from 2000 to 2016 were generated. Regression analysis was performed among lung cancer patients to explore the association between survival time and treatment utilization (chemotherapy, radiation, and surgery). A regression model was also applied to explore the association between treatment modalities and odds of dying. Results: A total of 826,217 patients were diagnosed with lung cancer between 2000-2016. The number of lung cancer cases increased by 7%, and the average annual frequency was 48,529 cases per year. Survival, mortality, and treatment utilization varied over the years based on demographic, clinical characteristics, and social status. Five-year survival rate was less than 10% among the study population, and 84% of included lung cancer patients died. Chemotherapy was more commonly used (62%), followed by radiation (35%) and surgical interventions (22%). Chemotherapy and surgery showed a survival advantage. The odds of dying were two times higher among patients treated with surgery than those who were not (OR: 2.62, 95%Cl: 2.58-2.67). Conclusion: This study highlighted the importance of considering treatment modalities and individual patient characteristics, which may impact survival times and mortality rates among older lung cancer patients.

Incorporating health equity into value assessment: frameworks, promising alternatives, and future directions.

Exploring methods that value diverse perspectives is critical to better understand the value of health equity in value assessment frameworks. In this paper, we examined emerging value assessment frameworks in the United States and present examples where evidence on outcomes and preferences for value do not take into consideration diverse perspectives. We identify possible solutions to improve existing value assessment methods and illustrate-using a hypothetical shared decision-making case study-an alternative to current value-assessment frameworks, "equitable multicriteria decision analysis," which could be implemented in the context of the value-based assessment of prevention choices for women at high risk of developing breast cancer. These proposed alternatives and solutions can be used by researchers and decision makers to incorporate health equity into value assessment. DISCLOSURES: No funding was received for this study. The authors have no conflicts of interest to report.

Cost-effectiveness of treatments for HER2-positive metastatic breast cancer and associated metastases: an overview of systematic reviews.

Introduction: Treatment of human epithelial growth factor receptor 2 (HER2)-positive breast cancer has rapidly evolved over the past decades with the addition of trastuzumab, lapatinib, pertuzumab, and trastuzumab emtansine (T-DM1). These treatments have dramatically impacted the survival of HER2-positive metastatic breast cancer (mBC) patients. Nonetheless, these agents are associated with high price tags, begging the question, 'Are treatments for HER2-positive metastatic breast cancer and associated metastases cost-effective'?Areas covered: We examine evidence on the cost-effectiveness of treatments for HER2-positive metastatic breast cancer and associated metastases through a review of systematic reviews on the topic. Additionally, we discuss the implications of our findings and provide recommendations for future directions in the assessment of the cost-effectiveness of targeted directed agents for HER2-positive mBC.Expert opinion: Heterogeneous evidence from cost-effectiveness studies on the use of targeted directed agents for HER2-positive mBC across the world caution against cross-country comparisons of the value of such treatments. It also militates in favor of the production and use of cost-effectiveness analyses for local rather than global decision-making, thus ensuring that economic evaluations reflect the needs of local decision-makers and populations for which they are devised.

Real-World Clinical and Economic Outcomes Associated with Palbociclib for HR-Positive/HER2 Negative Metastatic Breast Cancer: A Commentary.

Despite the achieved advancement in pharmacological cancer treatments, the majority of postmenopausal women with hormone receptor-positive metastatic breast cancer (mBC) will experience disease progression. Research into alternative therapies with improved efficacy and reduced side effects has led to the development of a new class of oral anticancer medications, the cyclin-dependent kinase (CDK) 4/6 inhibitors, which include palbociclib, ribociclib, and abemaciclib. Nonetheless, there is growing evidence that the effectiveness of oral anticancer medications is sub-optimal, being influenced by low adherence, sociodemographic factors, and adverse effect profiles. In addition, there is a disconnect between the high price tags of CDK 4/6 inhibitors and their observed effectiveness, raising questions about their value. Currently, the existing knowledge base on the effectiveness and cost-effectiveness of newer oral anticancer medications in understudied populations with possible health disparities is scant. This commentary discusses what is known about palbociclib's clinical effectiveness, safety, and adherence and suggests the need for further studies of real-world effectiveness and cost-effectiveness to help establish the value of newer oncologic drugs, such as palbociclib. DISCLOSURES: No funding supported the writing of this article. The authors have nothing to disclose.

Dataset used in the economic evaluation trastuzumab-based regimens for HER-2 positive metastatic breast cancer patients in the Taiwanese healthcare setting.

The present data article aims to describe the input parameters for a Markov model assessing the cost-effectiveness of four treatment sequences for patients with HER-2 positive metastatic breast cancer. The model input parameters include costs for physician visits, drugs, adverse event management, computed tomography (CT) scan, laboratory tests, echocardiogram, utilities, disutilities as well as the shape and scale parameters of a log-logistic distribution used for the transition probabilities.

A cost-effectiveness analysis of trastuzumab-containing treatment sequences for HER-2 positive metastatic breast cancer patients in Taiwan.

OBJECTIVE: Treatment options for HER-2-positive metastatic breast cancer (mBC) patients have expanded markedly since trastuzumab approval in 1998. Several other regimens are now available, including pertuzumab plus trastuzumab plus docetaxel, T-DM1, capecitabine plus lapatinib, and trastuzumab plus lapatinib. This study assesses the cost-effectiveness of four treatment sequences for HER-2-positive mBC according to the Taiwanese National Health Insurance Administration (TNHIA). METHODS: Costs (U.S. Dollars) and effectiveness (quality-adjusted life years) of four treatment sequences for HER-2-positive mBC patients were examined using a Markov model over a lifetime horizon. Transition probabilities, disease progression, and probability of adverse events and survival were derived from clinical trial data. Costs and health utilities were estimated from TNHIA, Taipei Medical University Hospital, and the literature. Deterministic, probabilistic sensitivity analyses and a scenario analysis examined parameter uncertainty and accounted for drug wastage in dosage and cost calculations. RESULTS: Sequence 3 (1st line: trastuzumab plus docetaxel; 2nd line: T-DM1; 3rd line: trastuzumab plus lapatinib) was the most cost-effective sequence followed by sequence 1 (1st line: pertuzumab plus trastuzumab plus docetaxel; 2nd line: T-DM1; 3rd line: capecitabine plus lapatinib), and sequence 4 (1st line: trastuzumab plus docetaxel; 2nd line: trastuzumab plus lapatinib; 3rd line: trastuzumab plus capecitabine), respectively. The model was sensitive to costs and transition probabilities, but not particularly sensitive to the wastage assumption. CONCLUSIONS: From the perspective of the TNHIA, trastuzumab plus docetaxel as 1st line followed by T-DM1 and trastuzumab plus lapatinib as 2nd and 3rd line represents the most cost-effective strategy among the four sequences considered for treating HER-2-positive mBC patients.