Preclinical Alzheimer Disease Drug Development: Early Considerations Based on Phase 3 Clinical Trials.

The number of people in the United States living with Alzheimer disease (AD) is growing, resulting in significant clinical and economic impact. Substantial research investment has led to drug development in stages of AD before symptomatic dementia, such as preclinical AD. Although there are no treatments approved for preclinical AD, there are currently 6 phase 3 clinical trials for preclinical AD treatments. In this article, we review these clinical trials and highlight considerations for future coverage decisions. In line with the definition of preclinical AD, enrollment in these trials focuses on cognitively unimpaired patients that are at high risk of AD because of family history and then genetic testing or brain imaging. Enrollment in most of these trials also allows for younger patients, including those aged under 65 years. Primary clinical trial endpoints focus on cognition often 4 or more years after treatment. Secondary endpoints include other measures of cognition and function, as well as biomarkers. Review of these trials brings to light a few potential considerations when covering these new medications in the future. First, novel and potentially costly approaches involving genetic testing and/or positron emission tomography imaging may be needed to identify appropriate patients and should be developed efficiently. Second, the long duration of these clinical trials suggest that there may be a need for alternative payment approaches in the United States that encourage early payers to pay for a medication for which the long-term benefits may not be realized until after the beneficiary is no longer with the health plan. Third, the value of AD treatments may differ across populations, creating a potential role for indication-based or population-based contracting. Finally, considering the potentially high budgetary impact and little real-world evidence for a new drug class, payers and manufacturers may want to consider outcomes-based payment approaches and coverage with evidence development to mitigate uncertainty about the value of the treatment demonstrated in well-defined populations in clinical trials versus more heterogeneous real-world settings. DISCLOSURES: This work was funded through a generous gift from the Global CEO Initiative on Alzheimer Disease. Hung reports grants from Agency for Healthcare Research and Quality and Pharmaceutical Research and Manufacturers of America outside the submitted work and past employment at CVS Health and BlueCross BlueShield Association. McClellan is an independent board member on the boards of Johnson & Johnson, Cigna, Alignment Healthcare, and Seer; co-chairs the Accountable Care Learning Collaborative and the Guiding Committee for the Health Care Payment Learning and Action Network; and receives fees for serving as an advisor for Cota and MITRE. Hamilton Lopez and Schneider have nothing to disclose. Part of this work was presented at the 2019 AMCP Nexus Meeting, October 29-November 1, 2019, in National Harbor, MD.

Empowering phase II clinical trials to reduce phase III failures.

The large number of failures in phase III clinical trials, which occur at a rate of approximately 45%, is studied herein relative to possible countermeasures. First, the phenomenon of failures is numerically described. Second, the main reasons for failures are reported, together with some generic improvements suggested in the related literature. This study shows how statistics explain, but do not justify, the high failure rate observed. The rate of failures due to a lack of efficacy that are not expected, is considered to be at least 10%. Expanding phase II is the simplest and most intuitive way to reduce phase III failures since it can reduce phase III false negative findings and launches of phase III trials when the treatment is positive but suboptimal. Moreover, phase II enlargement is discussed using an economic profile. As resources for research are often limited, enlarging phase II should be evaluated on a case-by-case basis. Alternative strategies, such as biomarker-based enrichments and adaptive designs, may aid in reducing failures. However, these strategies also have very low application rates with little likelihood of rapid growth.

Alternative Weighting Approaches for Anchored Matching-Adjusted Indirect Comparisons via a Common Comparator.

BACKGROUND: Adjusted indirect comparisons (anchored via a common comparator) are an integral part of health technology assessment. These methods are challenged when differences between studies exist, including inclusion/exclusion criteria, outcome definitions, patient characteristics, as well as ensuring the choice of a common comparator. OBJECTIVES: Matching-adjusted indirect comparison (MAIC) can address these challenges, but the appropriate application of MAICs is uncertain. Examples include whether to match between individual-level data and aggregate-level data studies separately for treatment arms or to combine the arms, which matching algorithm should be used, and whether to include the control treatment outcome and/or covariates present in individual-level data. RESULTS: Results from seven matching approaches applied to a continuous outcome in six simulated scenarios demonstrated that when no effect modifiers were present, the matching methods were equivalent to the unmatched Bucher approach. When effect modifiers were present, matching methods (regardless of approach) outperformed the Bucher method. Matching on arms separately produced more precise estimates compared with matching on total moments, and for certain scenarios, matching including the control treatment outcome did not produce the expected effect size. The entropy balancing approach was used to determine whether there were any notable advantages over the method proposed by Signorovitch et al. When unmeasured effect modifiers were present, no approach was able to estimate the true treatment effect. CONCLUSIONS: Compared with the Bucher approach (no matching), the MAICs examined demonstrated more accurate estimates, but further research is required to understand these methods across an array of situations.

Value of External Data in the Extrapolation of Survival Data: A Study Using the NJR Data Set.

BACKGROUND: Extrapolation of time-to-event data can be a critical component of cost-effectiveness analysis. OBJECTIVES: To contrast the value of external data on treatment effects as a selection aid in model fitting to the clinical data or for the direct extrapolation of survival. METHODS: We assume the existence of external summary data on both treatment and control and consider two scenarios: availability of external individual patient data (IPD) on the control only and an absence of external IPD. We describe how the summary data can be used to extrapolate survival or to assess the plausibility of extrapolations of the clinical data. We assess the merit of either approach using a comparison of cemented and cementless total hip replacement as a case study. Merit is judged by comparing incremental net benefit (INB) obtained in scenarios with incomplete IPD with that derived from modeling external IPD on both treatment and control. RESULTS: Measures of fit with the external summary data did not identify survival model specifications that best estimated INB. Addition of external IPD for the control only did not improve estimates of INB. Extrapolation of survival using the external summary data comparing treatment and control improved estimates of INB. CONCLUSIONS: Our case study indicates that summary data comparing treatment and control are more valuable than IPD limited to the control when extrapolating event rates for cost-effectiveness analysis. These data are best exploited in direct extrapolation of event rates rather than as an aid to select extrapolations on the basis of the clinical data.

On Enrichment Strategies for Biomarker Stratified Clinical Trials.

In the era of precision medicine, drugs are increasingly developed to target subgroups of patients with certain biomarkers. In large all-comer trials using a biomarker stratified design, the cost of treating and following patients for clinical outcomes may be prohibitive. With a fixed number of randomized patients, the efficiency of testing certain treatments parameters, including the treatment effect among biomarker-positive patients and the interaction between treatment and biomarker, can be improved by increasing the proportion of biomarker positives on study, especially when the prevalence rate of biomarker positives is low in the underlying patient population. When the cost of assessing the true biomarker is prohibitive, one can further improve the study efficiency by oversampling biomarker positives with a cheaper auxiliary variable or a surrogate biomarker that correlates with the true biomarker. To improve efficiency and reduce cost, we can adopt an enrichment strategy for both scenarios by concentrating on testing and treating patient subgroups that contain more information about specific treatment parameters of primary interest to the investigators. In the first scenario, an enriched biomarker stratified design enriches the cohort of randomized patients by directly oversampling the relevant patients with the true biomarker, while in the second scenario, an auxiliary-variable-enriched biomarker stratified design enriches the randomized cohort based on an inexpensive auxiliary variable, thereby avoiding testing the true biomarker on all screened patients and reducing treatment waiting time. For both designs, we discuss how to choose the optimal enrichment proportion when testing a single hypothesis or two hypotheses simultaneously. At a requisite power, we compare the two new designs with the BSD design in terms of the number of randomized patients and the cost of trial under scenarios mimicking real biomarker stratified trials. The new designs are illustrated with hypothetical examples for designing biomarker-driven cancer trials.

Evaluating biomarkers for prognostic enrichment of clinical trials.

BACKGROUND/AIMS: A potential use of biomarkers is to assist in prognostic enrichment of clinical trials, where only patients at relatively higher risk for an outcome of interest are eligible for the trial. We investigated methods for evaluating biomarkers for prognostic enrichment. METHODS: We identified five key considerations when considering a biomarker and a screening threshold for prognostic enrichment: (1) clinical trial sample size, (2) calendar time to enroll the trial, (3) total patient screening costs and the total per-patient trial costs, (4) generalizability of trial results, and (5) ethical evaluation of trial eligibility criteria. Items (1)-(3) are amenable to quantitative analysis. We developed the Biomarker Prognostic Enrichment Tool for evaluating biomarkers for prognostic enrichment at varying levels of screening stringency. RESULTS: We demonstrate that both modestly prognostic and strongly prognostic biomarkers can improve trial metrics using Biomarker Prognostic Enrichment Tool. Biomarker Prognostic Enrichment Tool is available as a webtool at http://prognosticenrichment.com and as a package for the R statistical computing platform. CONCLUSION: In some clinical settings, even biomarkers with modest prognostic performance can be useful for prognostic enrichment. In addition to the quantitative analysis provided by Biomarker Prognostic Enrichment Tool, investigators must consider the generalizability of trial results and evaluate the ethics of trial eligibility criteria.

The association of funding source on effect size in randomized controlled trials: 2013-2015 - a cross-sectional survey and meta-analysis.

BACKGROUND: Trials financed by for-profit organizations have been associated with favorable outcomes of new treatments, although the effect size of funding source impact on outcome is unknown. The aim of this study was to estimate the effect size for a favorable outcome in randomized controlled trials (RCTs), stratified by funding source, that have been published in general medical journals. METHODS: Parallel-group RCTs published in The Lancet, New England Journal of Medicine, and JAMA between 2013 and 2015 were identified. RCTs with binary primary endpoints were included. The primary outcome was the OR of patients' having a favorable outcome in the intervention group compared with the control group. The OR of a favorable outcome in each trial was calculated by the number of positive events that occurred in the intervention and control groups. A meta-analytic technique with random effects model was used to calculate summary OR. Data were stratified by funding source as for-profit, mixed, and nonprofit. Prespecified sensitivity, subgroup, and metaregression analyses were performed. RESULTS: Five hundred nine trials were included. The OR for a favorable outcome in for-profit-funded RCTs was 1.92 (95% CI 1.72-2.14), which was higher than mixed source-funded RCTs (OR 1.34, 95% CI 1.25-1.43) and nonprofit-funded RCTs (OR 1.32, 95% CI 1.26-1.39). The OR for a favorable outcome was higher for both clinical and surrogate endpoints in for-profit-funded trials than in RCTs with other funding sources. Excluding drug trials lowered the OR for a favorable outcome in for-profit-funded RCTs. The OR for a favorable surrogate outcome in drug trials was higher in for-profit-funded trials than in nonprofit-funded trials. CONCLUSIONS: For-profit-funded RCTs have a higher OR for a favorable outcome than nonprofit- and mixed source-funded RCTs. This difference is associated mainly with the use of surrogate endpoints in for-profit-financed drug trials.

Detection limits and cost comparisons of human- and gull-associated conventional and quantitative PCR assays in artificial and environmental waters.

Some molecular methods for tracking fecal pollution in environmental waters have both PCR and quantitative PCR (qPCR) assays available for use. To assist managers in deciding whether to implement newer qPCR techniques in routine monitoring programs, we compared detection limits (LODs) and costs of PCR and qPCR assays with identical targets that are relevant to beach water quality assessment. For human-associated assays targeting Bacteroidales HF183 genetic marker, qPCR LODs were 70 times lower and there was no effect of target matrix (artificial freshwater, environmental creek water, and environmental marine water) on PCR or qPCR LODs. The PCR startup and annual costs were the lowest, while the per reaction cost was 62% lower than the Taqman based qPCR and 180% higher than the SYBR based qPCR. For gull-associated assays, there was no significant difference between PCR and qPCR LODs, target matrix did not effect PCR or qPCR LODs, and PCR startup, annual, and per reaction costs were lower. Upgrading to qPCR involves greater startup and annual costs, but this increase may be justified in the case of the human-associated assays with lower detection limits and reduced cost per sample.

The Medical Imaging & Technology Alliance conference on research endpoints appropriate for medicare coverage of new PET radiopharmaceuticals.

The outcomes of a 2011 Medical Imaging & Technology Alliance (MITA) conference helped shape considerations about what might be the most appropriate pathways for the regulatory and payment considerations of new PET radiopharmaceuticals. As follow-up to that conference, MITA convened a second conference of stakeholders to advise payers on what might be acceptable endpoints for clinical trials to support the coverage of novel PET agents. The conference involved experts on imaging and clinical research, providers of PET services, as well as representatives of interested medical societies, the PET industry, and the regulatory and payer communities. The principal outcome of their deliberations was that it was unrealistic to expect trials of new PET radiopharmaceuticals to directly demonstrate a health benefit. Rather, intermediate outcomes, such as a positive change in patient management, would be more efficient and appropriate.

The Medical Imaging & Technology Alliance conference on research endpoints appropriate for Medicare coverage of new PET radiopharmaceuticals.

The outcomes of a 2011 Medical Imaging & Technology Alliance (MITA) conference helped shape considerations about what might be the most appropriate pathways for the regulatory and payment considerations of new PET radiopharmaceuticals. As follow-up to that conference, MITA convened a second conference of stakeholders to advise payers on what might be acceptable endpoints for clinical trials to support the coverage of novel PET agents. The conference involved experts on imaging and clinical research, providers of PET services, as well as representatives of interested medical societies, the PET industry, and the regulatory and payer communities. The principal outcome of their deliberations was that it was unrealistic to expect trials of new PET radiopharmaceuticals to directly demonstrate a health benefit. Rather, intermediate outcomes, such as a positive change in patient management, would be more efficient and appropriate.

[HTA-Perspective: Challenges in the early assessment of new oncological drugs]. / HTA-Perspektive: Herausforderungen bei der Frühbewertung neuer Onkologika.

Oncologic drug therapies have gained wide attention in the context of health policy priority setting for serious and socially significant diseases with high human and monetary costs. Due to uncertainties and scepticism about the actual therapeutic importance of newly approved oncology products, an early assessment programme was already established in Austria in 2007. The assessment of new oncology products is thereby faced with special challenges, since study populations are frequently not representative or the study design is laid out in such a manner that a definitive assessment of patient-relevant endpoints is not possible (cross-overs after interim assessments, surrogate parameters as primary endpoints, uncontrolled studies or those with unrealistic comparators, invalidated post-hoc identified biomarkers). On account of these major uncertainties, even the European Medicines Agency (EMA) is already contemplating multi-stage, "adaptive" approvals, and national reimbursement institutions are increasingly working with outcome-oriented, conditional reimbursement. (As supplied by publisher).

Identifying patient-relevant endpoints among individuals with schizophrenia: an application of patient-centered health technology assessment.

OBJECTIVES: Schizophrenia imposes a great burden on society, and while evaluation should play an important role in informing society's efforts to alleviate these burdens, it is unclear what "endpoints" should be chosen as the objective of such analyses. The objectives of the study were to elicit endpoints directly from patients with schizophrenia, to ascertain whether patients are sufficiently cognoscente to express what endpoints are and are not important to them and to rank the relevant endpoints. METHODS: We applied principles of patient-centered health technology assessment to identify and value endpoints from the patient's perspective. Focus groups were conducted to elicit endpoints, using interpretive phenomalogical analysis (IPA) to guide the collection, analysis and interpretation of data. Patient interviews were subsequently used to elicit patient preference over endpoints. Respondents were presented with cards outlining the endpoints and asked to remove irrelevant cards. They where then asked to identify and rank their five most relevant endpoints in order of importance. Interviews were recorded for the purposed of triangulation, and data was analyzed using descriptive statistics. Patients were recruited from five geographically diverse cities in Germany. Eligibility required a diagnosis of schizophrenia by a physician and treatment with an antipsychotic medication for at least one year. Respondents were excluded if they were experiencing an acute episode. RESULTS: Thirteen endpoints emerged as important from the focus groups spanning side-effects, functional status, processes of care and clinical outcomes. Respondents could clearly identify relevant and irrelevant endpoints, and rank which factors were important to them. Triangulation between field notes of the ranking exercise and recordings confirmed that rankings were not arbitrary, but justified from the respondents' point of view. CONCLUSIONS: Patients with schizophrenia can express preferences over endpoints. Our results show that qualitative methods such as IPA can be used to identify factors, but ranking exercises provide a more robust method for ranking the importance of endpoints. Future research involving patients with schizophrenia ranking outcomes is needed to identify variations across patients and methods such as conjoint analysis could prove beneficial in identifying acceptable tradeoffs across endpoints.

Reported outcomes in major cardiovascular clinical trials funded by for-profit and not-for-profit organizations: 2000-2005.

CONTEXT: In surveys based on data available prior to 2000, clinical trials funded by for-profit organizations appeared more likely to report positive findings than those funded by not-for-profit organizations. Whether this situation has changed over the past 5 years or whether similar effects are present among jointly funded trials is unknown. OBJECTIVE: To determine in contemporary randomized cardiovascular trials the association between funding source and the likelihood of reporting positive findings. DESIGN: We reviewed 324 consecutive superiority trials of cardiovascular medicine published between January 1, 2000, and July 30, 2005, in JAMA, The Lancet, and the New England Journal of Medicine. MAIN OUTCOME MEASURE: The proportion of trials favoring newer treatments over the standard of care was evaluated by funding source. RESULTS: Of the 324 superiority trials, 21 cited no funding source. Of the 104 trials funded solely by not-for-profit organizations, 51 (49%) reported evidence significantly favoring newer treatments over the standard of care, whereas 53 (51%) did not (P = .80). By contrast, 92 (67.2%) of 137 trials funded solely by for-profit organizations favored newer treatments over standard of care (P<.001). Among 62 jointly funded trials, 35 (56.5%), an intermediate proportion, favored newer treatments. For 205 randomized trials evaluating drugs, the proportions favoring newer treatments were 39.5%, not-for-profit; 54.4%, jointly funded; and 65.5%, for-profit trials (P for trend across groups = .002). For the 39 randomized trials evaluating cardiovascular devices, the proportions favoring newer treatments were 50.0%, not-for-profit; 69.2%, jointly funded; and 82.4%, for-profit trials (P for trend across groups = .07). Regardless of funding source, trials using surrogate end points, such as quantitative angiography, intravascular ultrasound, plasma biomarkers, and functional measures were more likely to report positive findings (67%) than trials using clinical end points (54.1%; P = .02). CONCLUSIONS: Recent cardiovascular trials funded by for-profit organizations are more likely to report positive findings than trials funded by not-for-profit organizations, as are trials using surrogate rather than clinical end points. Trials jointly funded by not-for-profit and for-profit organizations appear to report positive findings at a rate approximately midway between rates observed in trials supported solely by one or the other of these entities.

Clinically applicable laboratory end-points for treating snakebite coagulopathy.

AIMS: To determine which coagulation tests best reflect the return of clotting function after snakebite venom induced consumptive coagulopathy (VICC). METHODS: Cases of snake envenoming were prospectively recruited to the Australian Snakebite Project (ASP). This study examined cases with VICC treated with antivenom and monitored with serial measures of clottable fibrinogen, prothrombin time (PT) and activated partial thromboplastin time (aPTT). The main outcome measures were times from antivenom treatment until a moderate recovery in the PT (<24 seconds), a measurable aPTT and detectable fibrinogen. RESULTS: Forty-six cases were examined, including 27 brown snakes with proven complete venom neutralisation by antivenom in 25, 16 tiger snake group and three taipans. The times from initial antivenom dose to recovery were: PT<24 seconds, median 9.2 hours (IQR 6.2-11.3 hours); measurable aPTT, median 5.2 hours (IQR 3.4-8.8 hours); and detectable fibrinogen, median 8.8 hours (IQR 5.4-11.7 hours). In 10 cases where fibrinogen was detectable earlier than recovery of the PT, the mean fibrinogen was 0.25 g/L (SD 0.10) compared with 0.6 g/L (SD 0.28) in the remaining 36 cases (p<0.0001), reflecting differing sensitivities between laboratories. In only three patients (7%) was fibrinogen measurable before the other two outcomes, using highly sensitive fibrinogen assays. CONCLUSION: The combination of the PT and aPTT is an effective, clinically available and cost-effective end-point for treating VICC, and may take longer to return to normal after venom neutralisation than previously believed. The fibrinogen assays that are generally in use do not provide any additional useful information.

Economic endpoints in clinical trials.

Healthcare decision makers are increasingly requesting information on the cost and cost-effectiveness of new medicines at the time of product launch. In order to provide this information, data on healthcare resource utilization and, in some cases, costs, may be collected in clinical trials. In this paper, we discuss some of the issues statisticians need to address when it is appropriate to include these economic endpoints in the trial. Several design issues are discussed, including the alternative types of and methods for collecting economic endpoint data, sample size and generalizability. Alternative approaches in the analysis of resource utilization, cost and cost-effectiveness are also presented. Finally, several of the analytic approaches are applied to actual data from a clinical trial.

The RTOG Outcomes Model: economic end points and measures.

Recognising the value added by economic evaluations of clinical trials and the interaction of clinical, humanistic and economic end points, the Radiation Therapy Oncology Group (RTOG) has developed an Outcomes Model that guides the comprehensive assessment of this triad of end points. This paper will focus on the economic component of the model. The Economic Impact Committee was founded in 1994 to study the economic impact of clinical trials of cancer care. A steep learning curve ensued with considerable time initially spent understanding the methodology of economic analysis. Since then, economic analyses have been performed on RTOG clinical trials involving treatments for patients with non-small cell lung cancer, locally-advanced head and neck cancer and prostate cancer. As the care of cancer patients evolves with time, so has the economic analyses performed by the Economic Impact Committee. This paper documents the evolution of the cost-effectiveness analyses of RTOG from performing average cost-utility analysis to more technically sophisticated Monte Carlo simulation of Markov models, to incorporating prospective economic analyses as an initial end point. Briefly, results indicated that, accounting for quality-adjusted survival, concurrent chemotherapy and radiation for the treatment of non-small cell lung cancer, more aggressive radiation fractionation schedules for head and neck cancer and the addition of hormone therapy to radiation for prostate cancer are within the range of economically acceptable recommendations. The RTOG economic analyses have provided information that can further inform clinicians and policy makers of the value added of new or improved treatments.