Evidence for Treatment-by-Biomarker interaction for FDA-approved Oncology Drugs with Required Pharmacogenomic Biomarker Testing

Baseline serum testosterone and differential efficacy of bipolar androgen therapy and enzalutamide in the randomized TRANSFORMER trial

Bipolar androgen therapy (BAT) is effective in a subset of metastatic castration-resistant prostate cancer (mCRPC) patients. Treatment selection biomarkers are needed due to other therapies that can be equally efficacious. We performed post-hoc analysis to determine whether baseline serum testosterone (T) is a treatment selection marker in the TRANSFORMER study, a randomized trial of abiraterone-pretreated mCRPC patients assigned to BAT (n = 94) or enzalutamide (n = 101). The findings suggest that patients with poor outcomes to abiraterone and serum T ≥ 20 ng/dL may benefit preferentially from BAT over enzalutamide. Baseline testosterone could be considered in the treatment selection process when BAT is an option.

The impact of conventional cost-effectiveness analysis on pricing dynamics in the market of new medicines: a proposed countervailing approach

BACKGROUND

Countries using cost effectiveness ratio as a decision tool for price and reimbursement decisions still witness accelerating price increases. The objective of this paper is to propose a change in the application of the incremental cost effectiveness ratio as a criterion for price policy.

RESEARCH DESIGN

We develop a model that sets a price for marginal effectiveness equal to the marginal willingness to pay, but it reimburses average effectiveness according to the size of increased QALY gain.

RESULTS

This new formula also allows to split the economic value of drug between patients and the industry and creates a reward to invest into QALY gains. We show some empirical data of the new prices derived from the application of the new formula, as well as the implications in terms of the consumer and manufacturer´s surplus based on two potential scenarios of the incentives generated by this new formulation.

DISCUSSION

We propose that small increases in life expectancy be priced differently from substantial as a way of containing the price dynamics.

CONCLUSIONS

A change in the application of the ICER threshold will help to reduce the price pressure on public budgets.

Trends in the Quality of Evidence Supporting FDA Drug Approvals: Results from a Literature Review

CONTEXT

New drug approvals in the United States must be supported by substantial evidence from "adequate and well-controlled" trials. The Food and Drug Administration (FDA) has flexibility in how it applies this standard.

METHODS

The authors conducted a systematic literature review of studies evaluating the design and outcomes of the key trials supporting new drug approvals in the United States. They extracted data on the trial characteristics, endpoint types, and expedited regulatory pathways.

FINDINGS

Among 48 publications eligible for inclusion, 30 covered trial characteristics, 23 covered surrogate measures, and 30 covered regulatory pathways. Trends point toward less frequent randomization, double-blinding, and active controls, with variation by drug type and indication. Surrogate measures are becoming more common but are not consistently well correlated with clinical outcomes. Drugs approved through expedited regulatory pathways often have less rigorous trial design characteristics.

CONCLUSIONS

The characteristics of trials used to approve new drugs have evolved over the past two decades along with greater use of expedited regulatory pathways and changes in the nature of drugs being evaluated. While flexibility in regulatory standards is important, policy changes can emphasize high-quality data collection before or after FDA approval.

Physical activity moderates the association between white matter hyperintensity burden and cognitive change

Objective

Greater physical activity (PA) could delay cognitive decline, yet the underlying mechanisms remain unclear. White matter hyperintensity (WMH) burden is one of the key brain pathologies that have been shown to predict faster cognitive decline at a late age. One possible pathway is that PA may help maintain cognition by mitigating the detrimental effects of brain pathologies, like WMH, on cognitive change. This study aims to examine whether PA moderates the association between WMH burden and cognitive change.

Materials and methods

This population-based longitudinal study included 198 dementia-free adults aged 20-80 years. Leisure-time physical activity (LTPA) was assessed by a self-reported questionnaire. Occupational physical activity (OPA) was a factor score measuring the physical demands of each job. Total physical activity (TPA) was operationalized as the average of z-scores of LTPA and OPA. Outcome variables included 5-year changes in global cognition and in four reference abilities (fluid reasoning, processing speed, memory, and vocabulary). Multivariable linear regression models were used to estimate the moderation effect of PA on the association between white matter hyperintensities and cognitive change, adjusting for age, sex, education, and baseline cognition.

Results

Over approximately 5 years, global cognition (p < 0.001), reasoning (p < 0.001), speed (p < 0.001), and memory (p < 0.05) scores declined, and vocabulary (p < 0.001) increased. Higher WMH burden was correlated with more decline in global cognition (Spearman's rho = -0.229, p = 0.001), reasoning (rho = -0.402, p < 0.001), and speed (rho = -0.319, p < 0.001), and less increase in vocabulary (rho = -0.316, p < 0.001). Greater TPA attenuated the association between WMH burden and changes in reasoning (βTPA^*WMH = 0.029, 95% CI = 0.006-0.052, p = 0.013), speed (βTPA^*WMH = 0.035, 95% CI = -0.004-0.065, p = 0.028), and vocabulary (βTPA^*WMH = 0.034, 95% CI = 0.004-0.065, p = 0.029). OPA seemed to be the factor that exerted a stronger moderation on the relationship between WMH burden and cognitive change.

Conclusion

Physical activity may help maintain reasoning, speed, and vocabulary abilities in face of WMH burden. The cognitive reserve potential of PA warrants further examination.

The association between the presence of fast-food outlets and BMI: the role of neighbourhood socio-economic status, healthy food outlets, and dietary factors

Background

Evidence on the association between the presence of fast-food outlets and Body Mass Index (BMI) is inconsistent. Furthermore, mechanisms underlying the fast-food outlet presence-BMI association are understudied. We investigated the association between the number of fast-food outlets being present and objectively measured BMI. Moreover, we investigated to what extent this association was moderated by neighbourhood socio-economic status (NSES) and healthy food outlets. Additionally, we investigated mediation by frequency of fast-food consumption and amount of fat intake.

Methods

In this cross-sectional study, we used baseline data of adults in Lifelines (N = 149,617). Geo-coded residential addresses were linked to fast-food and healthy food outlet locations. We computed the number of fast-food and healthy food outlets within 1 kilometre (km) of participants’ residential addresses (each categorised into null, one, or at least two). Participants underwent objective BMI measurements. We linked data to Statistics Netherlands to compute NSES. Frequency of fast-food consumption and amount of fat intake were measured through questionnaires in Lifelines. Multivariable multilevel linear regression analyses were performed to investigate associations between fast-food outlet presence and BMI, adjusting for individual and environmental potential confounders. When exposure-moderator interactions had p-value < 0.10 or improved model fit (∆AIC ≥ 2), we conducted stratified analyses. We used causal mediation methods to assess mediation.

Results

Participants with one fast-food outlet within 1 km had a higher BMI than participants with no fast-food outlet within 1 km (B = 0.11, 95% CI: 0.01, 0.21). Effect sizes for at least two fast-food outlets were larger in low NSES areas (B = 0.29, 95% CI: 0.01, 0.57), and especially in low NSES areas where at least two healthy food outlets within 1 km were available (B = 0.75, 95% CI: 0.19, 1.31). Amount of fat intake, but not frequency of fast-food consumption, explained this association for 3.1%.

Conclusions

Participants living in low SES neighbourhoods with at least two fast-food outlets within 1 km of their residential address had a higher BMI than their peers with no fast-food outlets within 1 km. Among these participants, healthy food outlets did not buffer the potentially unhealthy impact of fast-food outlets. Amount of fat intake partly explained this association. This study highlights neighbourhood socio-economic inequalities regarding fast-food outlets and BMI.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13826-1.

Predictive value of chromosome 18q11.2-q12.1 loss for benefit from bevacizumab in metastatic colorectal cancer; a post-hoc analysis of the randomized phase III-trial AGITG-MAX

The VEGF‐A monoclonal antibody bevacizumab is currently recommended for first‐line treatment of all metastatic colorectal cancer (mCRC) patients. Cost‐benefit ratio and side‐effects however necessitate patient selection. A large retrospective yet nonrandomized study showed that patients with loss of chromosome 18q11.2‐q12.1 in the tumor and treated with bevacizumab have 3 months improved median progression‐free (PFS) and overall survival (OS) benefit compared to patients without this loss and/or treatment modality. Implementation for loss of chromosome 18q11.2‐q12.1 as a marker in clinical practice mandates evidence in a randomized controlled trial for bevacizumab. Of the trials with randomization of chemotherapy vs chemotherapy with bevacizumab, the AGITG‐MAX trial was the only one with tumor materials available. Chromosome 18q11.2‐q12.1 copy number status was measured for 256 AGITG‐MAX trial patients and correlated with PFS according to a predefined analysis plan with marker‐treatment interaction as the primary end‐point. Chromosome 18q11.2‐q12.1 losses were detected in 71% of patients (181/256) characteristic for mCRC. Consistent with the nonrandomized study, significant PFS benefit of bevacizumab was observed in patients with chromosome 18q11.2‐q12.1 loss (P = .009), and not in patients without 18q loss (P = .67). Although significance for marker‐treatment interaction was not reached (P_interaction = .28), hazard ratio and 95% confidence interval of this randomized cohort (HR_interaction = 0.72; 95% CI = 0.39‐1.32) shows striking overlap with the nonrandomized study cohorts (HR_interaction = 0.41; 95% CI = 0.32‐0.8) supported by a nonsignificant Cochrane χ² test (P = .11) for heterogeneity. We conclude that post hoc analysis of the AGITG‐MAX RCT provides supportive evidence for chromosome 18q11.2‐q12.1 as a predictive marker for bevacizumab in mCRC patients.

Quality of biomarker defined subgroups in FDA approvals of PD-1/PD-L1 inhibitors 2014-2020

PD-L1 expression is associated with differential response in cancers treated with checkpoint inhibitors. Clinical trials for FDA approvals of PD-1/PD-L1 inhibitors include limited subgroup analyses based on PD-L1 expression. We aimed to define the characteristics of PD-L1 defined subgroups of clinical trials leading to FDA approvals for new indications of PD-1/PD-L1 inhibitors. FDA approvals for PD-1/PD-L1 inhibitors from January 2014 to December 2020 were identified and the clinical trials leading to each drug approval were reviewed. We collected key variables from publicly available information on FDA website and peer-reviewed publications of clinical trials. We assessed regulatory characteristics (approval date, approved drug[s], cancer type, line of therapy, biomarker-restricted approval criteria) of each approval. Clinical trials leading to approvals were reviewed for trial design (RCT vs single arm study, primary endpoint) and PD-L1 defined subgroup design (no subgroup analysis, single threshold 2-group analysis, nested subgroups, and adjacent subgroups). We then compared regulatory and trials characteristics (trial design, primary endpoint, biomarker approval criteria) between studies with nested and adjacent subgroups. There were 60 approvals for PD-1/PD-L1 inhibitors between January 2014 and December 2020. Twelve of 60 (20%) did not include any PD-L1 subgroups. Twenty-five of 60 (42%) approvals reported only 2 subgroups, 14 (23%) included adjacent subgroups and 9 (15%) had nested subgroups. Twenty-five of 60 trials (42%) are single arm studies. Comparison of characteristics between trials with nested subgroup design and adjacent subgroup design did not show differences. We conclude that approvals for new indications of PD-1/PD-L1 inhibitors are based on studies that do not include comprehensive reporting of outcomes by PD-L1 biomarker subgroups. This article is protected by copyright. All rights reserved.

Association Between Mediterranean Diet and Functional Status in Older Adults: A Longitudinal Study Based on the Washington Heights-Inwood Columbia Aging Project

BACKGROUND

Current evidence on the association between Mediterranean diet (MeDi) intake and activities of daily living (ADL) is limited and inconsistent in older adults.

METHODS

This study included 1 696 participants aged ≥65 years in the Washington Heights-Inwood Community Aging Project study. The MeDi score was calculated based on data collected from the Willett's semiquantitative food frequency questionnaire. The multivariable-adjusted Cox regression model was applied to examine the association of MeDi score with risks of disability in basic (BADL) and instrumental ADL (IADL), as well as the overall ADL (B-IADL).

RESULTS

Eight hundred and thirty-two participants with incident ADL disability were identified over a median follow-up of 5.39 years. The continuous MeDi score was significantly associated with decreased risk of disability in B-IADL (hazard ratio = 0.95, 95% confidence interval = 0.91-0.99, p = .018) in a model adjusted for age, sex, race/ethnicity, educational level, and dietary calories intake but was no longer significant after additionally adjusted for multiple comorbidities and physical activities (0.97 [0.93, 1.01], p = .121). The continuous MeDi score was significantly associated with decreased risk of disability in B-IADL (0.92 [0.85, 1.00], p = .043) and BADL (0.90 [0.82, 0.99], p = .030) in non-Hispanic Whites, but not in non-Hispanic Blacks and Hispanics (p > .05 for all).

CONCLUSIONS

Higher MeDi score was associated with decreased risk of ADL disability, particularly in non-Hispanic Whites.

The evidence landscape in precision medicine

Precision medicine is beginning to make an impact on the treatment of different diseases, but there are still challenges that must be overcome, such as the complexity of interventions, the need for marker validation, and the level of evidence necessary to demonstrate effectiveness. In this Perspective, we describe how evidence landscapes can help to address these challenges.

Frequentist rules for regulatory approval of subgroups in phase III trials: A fresh look at an old problem

Background

The number of Phase III trials that include a biomarker in design and analysis has increased due to interest in personalised medicine. For genetic mutations and other predictive biomarkers, the trial sample comprises two subgroups, one of which, say B+ is known or suspected to achieve a larger treatment effect than the other B−. Despite treatment effect heterogeneity, trials often draw patients from both subgroups, since the lower responding B− subgroup may also gain benefit from the intervention. In this case, regulators/commissioners must decide what constitutes sufficient evidence to approve the drug in the B− population.

Methods and Results

Assuming trial analysis can be completed using generalised linear models, we define and evaluate three frequentist decision rules for approval. For rule one, the significance of the average treatment effect in B− should exceed a pre-defined minimum value, say ZB−>L. For rule two, the data from the low-responding group B− should increase statistical significance. For rule three, the subgroup-treatment interaction should be non-significant, using type I error chosen to ensure that estimated difference between the two subgroup effects is acceptable. Rules are evaluated based on conditional power, given that there is an overall significant treatment effect. We show how different rules perform according to the distribution of patients across the two subgroups and when analyses include additional (stratification) covariates in the analysis, thereby conferring correlation between subgroup effects.

Conclusions

When additional conditions are required for approval of a new treatment in a lower response subgroup, easily applied rules based on minimum effect sizes and relaxed interaction tests are available. Choice of rule is influenced by the proportion of patients sampled from the two subgroups but less so by the correlation between subgroup effects.

Pharmacogenomic Biomarkers in US FDA-Approved Drug Labels (2000-2020)

Pharmacogenomics (PGx) is a key subset of precision medicine that relates genomic variation to individual response to pharmacotherapy. We assessed longitudinal trends in US FDA approval of new drugs labeled with PGx information. Drug labels containing PGx information were obtained from Drugs@FDA and guidelines from PharmGKB were used to compare the actionability of PGx information in drug labels across therapeutic areas. The annual proportion of new drug approvals with PGx labeling has increased by nearly threefold from 10.3% (n = 3) in 2000 to 28.2% (n = 11) in 2020. Inclusion of PGx information in drug labels has increased for all clinical areas over the last two decades but most prominently for cancer therapies, which comprise the largest proportion (75.5%) of biomarker–drug pairs for which PGx testing is required. Clinically actionable information was more frequently observed in biomarker–drug pairs associated with cancer drugs compared to those for other therapeutic areas (n = 92 (59.7%) vs. n = 62 (40.3%), p < 0.0051). These results suggest that further evidence is needed to support the clinical adoption of pharmacogenomics in non-cancer therapeutic areas.

Economic considerations on the usage of biologics in the allergy clinic

The advent of biologic therapies has transformed care for severe atopic disorders but their high cost poses new challenges with regard to long-term sustainability and fair allocation of resources. This article covers the basic concepts of cost-utility analyses and reviews the available literature on cost utility of biologic drugs in atopic disorders. When used within their limits as part of a multi-dimensional assessment, economic analyses can be extremely useful to guide decision-making and prioritization of care. Despite the good quality of most cost-utility analyses conducted for the use of biologics in asthma and other atopic diseases, their conclusions regarding cost-effectiveness are extremely variable. This is mainly due to the use of inconsistent estimates of health utility benefit with therapy. Development of reliable and validated instruments to measure disutility in atopic disorders and measure of indirect costs in atopic disease are identified as a priority for future research.

Evaluation of precision medicine assessment reports of the Belgian healthcare payer to inform reimbursement decisions

INTRODUCTION

Precision medicines rely on companion diagnostics to identify patient subgroups eligible for receiving the pharmaceutical product. Until recently, the Belgian public health payer, RIZIV-INAMI, assessed precision medicines and companion diagnostics separately for reimbursement decisions. As both components are considered co-dependent technologies, their assessment should be conducted jointly from a health technology assessment (HTA) perspective. As of July 2019, a novel procedure was implemented accommodating for this joint assessment practice. The aim of this research was to formulate recommendations to improve the assessment in the novel procedure.

METHODS

This study evaluated the precision medicine assessment reports of RIZIV-INAMI of the last 5 years under the former assessment procedure. The HTA framework for co-dependent technologies developed by Merlin et al. for the Australian healthcare system was used as a reference standard in this evaluation. Criteria were scored as either present or not present.

RESULTS

Thirteen assessment reports were evaluated. Varying scores between reports were obtained for the domain establishing the co-dependent relationship between diagnostic and pharmaceutical. Domains evaluating the clinical utility of the biomarker and the cost-effectiveness performed poorly, whereas the budget impact and the transfer of trial data to the local setting performed well.

RECOMMENDATIONS

Based on these results we recommend three amendments for the novel procedure. (i) The implementation of the linked evidence approach when direct evidence of clinical utility is not present, (ii) incorporation of a bias assessment tool, and (iii) further specify guidelines for submission and assessment to decrease the variability of reported evidence between assessment reports.

Decision Support Systems in Oncology

Precision medicine is the future of health care: please watch the animation at https://vimeo.com/241154708. As a technology-intensive and -dependent medical discipline, oncology will be at the vanguard of this impending change. However, to bring about precision medicine, a fundamental conundrum must be solved: Human cognitive capacity, typically constrained to five variables for decision making in the context of the increasing number of available biomarkers and therapeutic options, is a limiting factor to the realization of precision medicine. Given this level of complexity and the restriction of human decision making, current methods are untenable. A solution to this challenge is multifactorial decision support systems (DSSs), continuously learning artificial intelligence platforms that integrate all available data—clinical, imaging, biologic, genetic, cost—to produce validated predictive models. DSSs compare the personalized probable outcomes—toxicity, tumor control, quality of life, cost effectiveness—of various care pathway decisions to ensure optimal efficacy and economy. DSSs can be integrated into the workflows both strategically (at the multidisciplinary tumor board level to support treatment choice, eg, surgery or radiotherapy) and tactically (at the specialist level to support treatment technique, eg, prostate spacer or not). In some countries, the reimbursement of certain treatments, such as proton therapy, is already conditional on the basis that a DSS is used. DSSs have many stakeholders—clinicians, medical directors, medical insurers, patient advocacy groups—and are a natural consequence of big data in health care. Here, we provide an overview of DSSs, their challenges, opportunities, and capacity to improve clinical decision making, with an emphasis on the utility in oncology.

Shedding Light on Reimbursement Policies of Companion Diagnostics in European Countries

OBJECTIVES

Ensuring access to precision medicine has been an issue because in some European countries, desynchronized reimbursement decision-making occurs between the medicine and the companion diagnostic (CDx). This has resulted in cases in which precision medicine is reimbursed but not the CDx. In overcoming this issue, an alignment of the decision-making process for reimbursement between the 2 entities should be considered. As pharmaceutical reimbursement procedures are meticulously covered in the literature, we set out to systematically map in vitro diagnostic (IVD) reimbursement procedures and identify policies for aligning these procedures with the pharmaceutical reimbursement procedures.

METHODS

We selected 8 European countries for this analysis. For each country, we characterized the national benefit basket entailing the IVD medical acts in outpatient care, evaluated the procedure for inclusion, and identified alternative reimbursement practices for CDx. Targeted searches, using publicly accessible sources, were conducted to identify relevant reimbursement policies and laws.

RESULTS

We systematically describe the reimbursement process in 8 European countries. Alternative procedures for CDx reimbursement were identified in Belgium and Germany. Alternative policies attributed to the practice of precision medicine were identified in England and Italy. In France, some CDx are included in the "coverage with evidence" development program. Specifically, the health technology assessment agencies of France and England commented on the assessment of companion diagnostics and their clinical utility.

CONCLUSION

CDx reimbursement procedures have recently been implemented in some countries. This was seemingly done primarily to ensure access to the precision medicine and only secondary to the value they would provide.

Impact of Molybdenum Compounds as Anticancer Agents

The aim of this mini review was to report the molybdenum compound intervention to control cancer disease. The intervention explains its roles and progress from inorganic molybdenum compounds via organomolybdenum complexes to its nanoparticles to control oesophageal cancer and breast cancer as case studies. Main contributions of molybdenum compounds as anticancer agents could be observed in their nanofibrous support with suitable physicochemical properties, combination therapy, and biosensors (biomarkers). Recent areas in anticancer drug design, which entail the uses of selected targets, were also surveyed and proposed.

Evidence to Support Inclusion of Pharmacogenetic Biomarkers in Randomised Controlled Trials

Pharmacogenetics and biomarkers are becoming normalised as important technologies to improve drug efficacy rates, reduce the incidence of adverse drug reactions, and make informed choices for targeted therapies. However, their wider clinical implementation has been limited by a lack of robust evidence. Suitable evidence is required before a biomarker’s clinical use, and also before its use in a clinical trial. We have undertaken a review of five pharmacogenetic biomarker-guided randomised controlled trials (RCTs) and evaluated the evidence used by these trials to justify biomarker inclusion. We assessed and quantified the evidence cited in published rationale papers, or where these were not available, obtained protocols from trial authors. Very different levels of evidence were provided by the trials. We used these observations to write recommendations for future justifications of biomarker use in RCTs and encourage regulatory authorities to write clear guidelines.

Systematic review: predictive biomarkers of therapeutic response in inflammatory bowel disease-personalised medicine in its infancy

BACKGROUND

Inflammatory bowel disease (IBD) is characterised by substantial heterogeneity in treatment response. With an expanding number of therapeutic agents, identifying optimal treatment at the patient level remains a major challenge.

AIM

To systematically review the available literature on predictive biomarkers of therapeutic response in IBD.

METHODS

An electronic literature search was performed on 30 January 2018 using MEDLINE, EMBASE and the Cochrane Library. Retrospective, prospective, uncontrolled and controlled studies reporting on biomarkers predicting therapeutic response in paediatric and adult IBD populations were eligible for inclusion. The methodological quality of the included studies was assessed using the QUIPS tool. Due to anticipated heterogeneity and limited data, a qualitative, rather than quantitative, assessment was planned.

RESULTS

Of the 10 638 citations identified, 92 articles met the inclusion criteria. Several potential DNA, mRNA and protein markers were evaluated as predictive biomarkers. Most studies focused on predicting response to anti-TNF agents. Substantial between-study heterogeneity was identified with respect to both the biomarkers studied and the definition of response. None of the included studies received a low risk of bias rating for all six domains. Currently, none of the biomarkers is sufficiently predictive for clinical use.

CONCLUSIONS

The search for predictive biomarkers is still in its infancy and current evidence is limited. Future research efforts should take into account the high patient heterogeneity within prospective trials with objective response assessment. Predictive models will most likely comprise a combination of several molecular markers from integrated omics-levels and clinical characteristics.

Exclusive Drug Labeling Rights as a New Incentive for Contribution to a Communal Biomarker Resource

Biomarkers are an important tool in modern drug development. The FDA has posited that increased use of biomarkers in clinical trials can accelerate pharmaceutical industry productivity, ushering new drugs to market. Accordingly, the FDA has created two pathways for evaluation of biomarker utility. Biomarkers incorporated into clinical trials, the traditional pathway, are effectively private to a therapeutic sponsor and to the scope of the trial. By contrast, in Biomarker Qualification ("BQ"), the second pathway, a biomarker is certified as a publicly available tool. The FDA has hoped that academic, non-profit, and industry stakeholders would work together in consortia to qualify biomarkers, cumulatively generating a common resource of broad utility. In practice, utilization of Biomarker Qualification has been paltry. Incentives for BQ that align with the interests of industry resource holders are necessary to fuel increased utilization of biomarkers in clinical trials and create the communal biomarker toolkit envisioned by the FDA. A blanket extension of exclusivity for any drug successfully paired with a companion biomarker would diminish public access to medicine by encouraging spurious biomarkers and correspondingly narrowed clinical trials. As a measured alternative, an exclusive right to include a qualified companion biomarker on an FDA drug label would balance public access externalities. This exclusivity would waylay label approval, and thus marketability, of later drugs relying on the qualified biomarker for clinical safety or efficacy. Accordingly, sponsors would find no incentive to portage an ineffective or unnecessary biomarker through clinical trials, as there would be no benefit to securing exclusive rights in a tool others saw no value in using.

Comparative effectiveness from a single-arm trial and real-world data: alectinib versus ceritinib

Aim: To compare the overall survival of anaplastic lymphoma kinase-positive non-small-cell lung cancer patients who received alectinib with those who received ceritinib. Materials & methods: Two treatment arms (alectinib [n = 183] and ceritinib [n = 67]) were extracted from clinical trials and an electronic health record database, respectively. Propensity scores were applied to balance baseline characteristics. Kaplan–Meier and multivariate Cox regression were conducted. Results: After propensity score adjustment, baseline characteristics were balanced. Alectinib had a prolonged median overall survival (alectinib = 24.3 months and ceritinib = 15.6 months) and lower risk of death (hazard ratio: 0.65; 95% CI: 0.48–0.88). Conclusion: Alectinib was associated with prolonged overall survival versus ceritinib, which is consistent with efficacy evidence from clinical trials.

Impact of Biomarker-based Design Strategies on the Risk of False-Positive Findings in Targeted Therapy Evaluation

PURPOSE

When there is more than one potentially predictive biomarker for a new drug, the drug is often evaluated in different subpopulations defined by different biomarkers. We aim to (i) estimate the risk of false-positive findings with this approach and (ii) evaluate the cross-validated adaptive signature design (CVASD) as a potential alternative.

EXPERIMENTAL DESIGN

By using numerically simulated data, we compare the current approach and the CVASD across different settings and scenarios. We consider three strategies for CVASD. The first two CVASD strategies are different in terms of the partitioning of the overall significance level (between the population test and the subgroup test). In the third CVASD strategy, the order of the two tests is reversed, that is, the population test is realized when the prioritized subgroup test is not statistically significant.

RESULTS

The current approach results in a high risk of false-positive findings, whereas this risk is close to the nominal level of 5% once applying the CVASD, regardless of the strategy. When the treatment is equally effective to all patients, only the CVASD strategies could specify correctly the absence of a sensitive subgroup. When the treatment is only effective for some sensitive responders, the third CVASD strategy stands out by its ability to correctly identify the predictive biomarker(s).

CONCLUSIONS

The drug-biomarker coevaluation based on a series of independent enrichment trials can result in a high risk of false-positive findings. CVASD with some appropriate adjustments can be a good alternative to overcome this multiplicity issue.

Protein biomarkers for subtyping breast cancer and implications for future research

INTRODUCTION

Breast cancer subtypes are currently defined by a combination of morphologic, genomic, and proteomic characteristics. These subtypes provide a molecular portrait of the tumor that aids diagnosis, prognosis, and treatment escalation/de-escalation options. Gene expression signatures describing intrinsic breast cancer subtypes for predicting risk of recurrence have been rapidly adopted in the clinic. Despite the use of subtype classifications, many patients develop drug resistance, breast cancer recurrence, or therapy failure. Areas covered: This review provides a summary of immunohistochemistry, reverse phase protein array, mass spectrometry, and integrative studies that are revealing differences in biological functions within and between breast cancer subtypes. We conclude with a discussion of rigor and reproducibility for proteomic-based biomarker discovery. Expert commentary: Innovations in proteomics, including implementation of assay guidelines and standards, are facilitating refinement of breast cancer subtypes. Proteomic and phosphoproteomic information distinguish biologically functional subtypes, are predictive of recurrence, and indicate likelihood of drug resistance. Actionable, activated signal transduction pathways can now be quantified and characterized. Proteomic biomarker validation in large, well-designed studies should become a public health priority to capitalize on the wealth of information gleaned from the proteome.