Real-world evidence and regulatory drug approval

Artificial intelligence to unlock real-world evidence in clinical oncology: A primer on recent advances

PURPOSE

Real world evidence is crucial to understanding the diffusion of new oncologic therapies, monitoring cancer outcomes, and detecting unexpected toxicities. In practice, real world evidence is challenging to collect rapidly and comprehensively, often requiring expensive and time-consuming manual case-finding and annotation of clinical text. In this Review, we summarise recent developments in the use of artificial intelligence to collect and analyze real world evidence in oncology.

METHODS

We performed a narrative review of the major current trends and recent literature in artificial intelligence applications in oncology.

RESULTS

Artificial intelligence (AI) approaches are increasingly used to efficiently phenotype patients and tumors at large scale. These tools also may provide novel biological insights and improve risk prediction through multimodal integration of radiographic, pathological, and genomic datasets. Custom language processing pipelines and large language models hold great promise for clinical prediction and phenotyping.

CONCLUSIONS

Despite rapid advances, continued progress in computation, generalizability, interpretability, and reliability as well as prospective validation are needed to integrate AI approaches into routine clinical care and real-time monitoring of novel therapies.

Harmonization of tumor mutation burden testing with comprehensive genomic profiling assays: an IQN Path initiative

BACKGROUND

Although conflicting results emerged from different studies, the tumor mutational burden (TMB) appears as one of most reliable biomarkers of sensitivity to immune checkpoint inhibitors. Several laboratories are reporting TMB values when performing comprehensive genomic profiling (CGP) without providing a clinical interpretation, due to the lack of validated cut-off values. The International Quality Network for Pathology launched an initiative to harmonize TMB testing with CGP assay and favor the clinical implementation of this biomarker.

METHODS

TMB evaluation was performed with three commercially available CGP panels, TruSight Oncology 500 (TSO500), Oncomine Comprehensive Plus Assay (OCA) and QIAseq Multimodal Panel (QIA), versus the reference assay FoundationOne CDx (F1CDx). Archived clinical samples derived from 60 patients with non-small cell lung cancer were used for TMB assessment. Adjusted cut-off values for each panel were calculated.

RESULTS

Testing was successful for 91.7%, 100%, 96.7% and 100% of cases using F1CDx, TSO500, OCA and QIA, respectively. The matrix comparison analysis, between the F1CDx and CGP assays, showed a linear correlation for all three panels, with a higher correlation between F1CDx and TSO500 (rho=0.88) than in the other two comparisons (rho=0.77 for QIA; 0.72 for OCA). The TSO500 showed the best area under the curve (AUC, value 0.96), with a statistically significant difference when compared with the AUC of OCA (0.83, p value=0.01) and QIA (0.88, p value=0.028). The Youden Index calculation allowed us to extrapolate TMB cut-offs of the different panels corresponding to the 10 mutations/megabase (muts/Mb) cut-off of F1CDx: 10.19, 10.4 and 12.37 muts/Mb for TSO500, OCA and QIA, respectively. Using these values, we calculated the relative accuracy measures for the three panels. TSO500 showed 86% specificity and 96% sensitivity, while OCA and QIA had lower yet similar values of specificity and sensitivity (73% and 88%, respectively).

CONCLUSION

This study estimated TMB cut-off values for commercially available CGP panels. The results showed a good performance of all panels on clinical samples and the calculated cut-offs support better accuracy measures for TSO500. The validated cut-off values can drive clinical interpretation of TMB testing in clinical research and clinical practice.

Innovations in Cancer Treatment of Children

Pediatric cancer outcomes have significantly improved, and yet this success is not spread equally across cancer types or patients. Disparities data in pediatric oncology highlight needed improvements in access to care, including clinical trials and advanced testing for all patients. For cancers such as brain tumors and sarcomas, continued advancement in understanding the biology of tumor heterogeneity is an essential step toward finding new therapeutic combinations to improve outcomes. Pediatric cancer survivors need access to emerging technologies aimed at reducing or better managing toxicities from therapy. With advances in treatment and survival, pediatric oncology patients continue to need longitudinal, multidisciplinary subspecialty care. Refining the communication between pediatric oncologists, primary pediatricians, survivorship clinics, and adult primary care is key in ensuring the best lifelong care of pediatric cancer survivors. In this State-of-The-Art review, we discuss 5 major domains in pediatric oncology: reducing toxicity, cancer biology, novel therapies, detection and monitoring, and access to care, to highlight recent advances and areas for continued improvement.

Evaluation of reporting quality of cohort studies using real-world data based on RECORD: systematic review

OBJECTIVE

Real-world data (RWD) and real-world evidence (RWE) have been paid more and more attention in recent years. We aimed to evaluate the reporting quality of cohort studies using real-world data (RWD) published between 2013 and 2021 and analyze the possible factors.

METHODS

We conducted a comprehensive search in Medline and Embase through the OVID interface for cohort studies published from 2013 to 2021 on April 29, 2022. Studies aimed at comparing the effectiveness or safety of exposure factors in the real-world setting were included. The evaluation was based on the REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement. Agreement for inclusion and evaluation was calculated using Cohen's kappa. Pearson chi-square test or Fisher's exact test and Mann-Whitney U test were used to analyze the possible factors, including the release of RECORD, journal IFs, and article citations. Bonferroni's correction was conducted for multiple comparisons. Interrupted time series analysis was performed to display the changes in report quality over time.

RESULTS

187 articles were finally included. The mean ± SD of the percentage of adequately reported items in the 187 articles was 44.7 ± 14.3 with a range of 11.1-87%. Of 23 items, the adequate reporting rate of 10 items reached 50%, and the reporting rate of some vital items was inadequate. After Bonferroni's correction, the reporting of only one item significantly improved after the release of RECORD and there was no significant improvement in the overall report quality. For interrupted time series analysis, there were no significant changes in the slope (p = 0.42) and level (p = 0.12) of adequate reporting rate. The journal IFs and citations were respectively related to 2 areas and the former significantly higher in high-reporting quality articles.

CONCLUSION

The endorsement of the RECORD cheklist was generally inadequate in cohort studies using RWD and has not improved in recent years. We encourage researchers to endorse relevant guidelines when utilizing RWD for research.

Commercializing Personal Health Information: A Critical Qualitative Content Analysis of Documents Describing Proprietary Primary Care Databases in Canada

BACKGROUND

Commercial data brokers have amassed large collections of primary care patient data in proprietary databases. Our study objective was to critically analyze how entities involved in the collection and use of these records construct the value of these proprietary databases. We also discuss the implications of the collection and use of these databases.

METHODS

We conducted a critical qualitative content analysis using publicly available documents describing the creation and use of proprietary databases containing Canadian primary care patient data. We identified relevant commercial data brokers, as well as entities involved in collecting data or in using data from these databases. We sampled documents associated with these entities that described any aspect of the collection, processing, and use of the proprietary databases. We extracted data from each document using a structured data tool. We conducted an interpretive thematic content analysis by inductively coding documents and the extracted data.

RESULTS

We analyzed 25 documents produced between 2013 and 2021. These documents were largely directed at the pharmaceutical industry, as well as shareholders, academics, and governments. The documents constructed the value of the proprietary databases by describing extensive, intimate, detailed patient-level data holdings. They provided examples of how the databases could be used by pharmaceutical companies for regulatory approval, marketing and understanding physician behaviour. The documents constructed the value of these data more broadly by claiming to improve health for patients, while also addressing risks to privacy. Some documents referred to the trade-offs between patient privacy and data utility, which suggests these considerations may be in tension.

CONCLUSION

Documents in our analysis positioned the proprietary databases as socially legitimate and valuable, particularly to pharmaceutical companies. The databases, however, may pose risks to patient privacy and contribute to problematic drug promotion. Solutions include expanding public data repositories with appropriate governance and external regulatory oversight.

Increasing patient participation in oncology clinical trials

AIM

Timely recruitment of eligible participants is essential for the success of clinical trials, with insufficient accrual being the leading cause for premature termination of both oncology and non-oncology trials.

METHODS

In this paper we further elaborate on the challenges for patient participation in oncology trials from physician, patient, healthcare system, and some trial-related perspectives.

RESULTS

We present strategies such as use of digital healthcare technologies, real-world data and real-world evidence, decentralized clinical trials, pragmatic trial designs, and supportive services to increase patient participation.

CONCLUSIONS

Multifaceted measures are necessary to increase patient participation, especially for those who are under-represented in cancer trials.

Outcomes of Chemoimmunotherapy Among Patients With Extensive-Stage Small Cell Lung Cancer According to Potential Clinical Trial Eligibility

IMPORTANCE

Chemoimmunotherapy is the standard first-line therapy for patients with extensive-stage small cell lung cancer (ES-SCLC). However, whether findings from pivotal trials can be extrapolated to the clinical practice setting remains unclear.

OBJECTIVE

To compare treatment outcome gaps following first-line chemoimmunotherapy for patients with ES-SCLC between those who met and did not meet the eligibility criteria used in previous clinical trials.

DESIGN, SETTING, AND PARTICIPANTS

A prospective cohort study was conducted from September 1, 2019, to September 30, 2020, at 32 hospitals in Japan, with at least 12 months of follow-up. Participants included consecutive patients with ES-SCLC who received carboplatin and etoposide with atezolizumab as first-line therapy.

EXPOSURES

Patients who met eligibility criteria for pivotal phase 3 clinical trials were considered trial-eligible.

MAIN OUTCOMES AND MEASURES

The primary outcome was 6-month progression-free survival. The secondary outcomes were differences in progression-free survival, overall survival, and safety according to whether key clinical trial eligibility criteria were met.

RESULTS

A total of 207 patients were analyzed (median age, 72 years; range, 46-87 years; 170 [82%] were male). Sixty-four patients (31%) were older adults (age ≥75 years), and most (184 [89%]) had an Eastern Cooperative Oncology Group performance status of 0 or 1. There were 132 (64%) trial-eligible patients. The 6-month progression-free survival rate for all patients was 38.8% (95% CI, 32.4%-45.7%). The median progression-free survival was 5.1 months in trial-eligible patients and 4.7 months in trial-ineligible patients (hazard ratio, 0.72; 95% CI, 0.53-0.97; P = .03). The proportion of patients who achieved disease control was 93% (118 of 127) in trial-eligible patients and 77% (55 of 71) in trial-ineligible patients (P = .002). The median overall survival was 15.8 months in trial-eligible patients and 13.1 months in trial-ineligible patients (hazard ratio, 0.73; 95% CI, 0.51-1.07; P = .10). The rate of severe adverse events was numerically higher among trial-ineligible patients than among trial-eligible patients (39% vs 27%; P = .07).

CONCLUSIONS AND RELEVANCE

In this cohort study, the overall treatment outcome was comparable to that reported in pivotal clinical trials. However, treatment outcomes after chemoimmunotherapy might differ between trial-eligible and trial-ineligible patients. These findings suggest that trial-eligibility criteria may be useful in clinical practice, and further studies using data from clinical practice settings are required to inform regulatory approval and clinical decision-making.

Fast Methods for Drug Approval: Research Perspectives for Pandemic Preparedness

Public heath emergencies such as the outbreak of novel infectious diseases represent a major challenge for drug regulatory bodies, practitioners, and scientific communities. In such critical situations drug regulators and public health practitioners base their decisions on evidence generated and synthesised by scientists. The urgency and novelty of the situation create high levels of uncertainty concerning the safety and effectiveness of drugs. One key tool to mitigate such emergencies is pandemic preparedness. There seems to be, however, a lack of scholarly work on methodology for assessments of new or existing drugs during a pandemic. Issues related to risk attitudes, evidence production and evidence synthesis for drug approval require closer attention. This manuscript, therefore, engages in a conceptual analysis of relevant issues of drug assessment during a pandemic. To this end, we rely in our analysis on recent discussions in the philosophy of science and the philosophy of medicine. Important unanswered foundational questions are identified and possible ways to answer them are considered. Similar problems often have similar solutions, hence studying similar situations can provide important clues. We consider drug assessments of orphan drugs and drug assessments during endemics as similar to drug assessment during a pandemic. Furthermore, other scientific fields which cannot carry out controlled experiments may guide the methodology to draw defeasible causal inferences from imperfect data. Future contributions on methodologies for addressing the issues raised here will indeed have great potential to improve pandemic preparedness.

A Comparison of Seven Oncology External Control Arm Case Studies: Critiques From Regulatory and Health Technology Assessment Agencies

OBJECTIVES

The development of accelerated approval programs for high morbidity and unmet need conditions has driven the use of single-arm studies in drug development. Regulatory and health technology assessment (HTA) agencies are recognizing that high-quality external control arms (ECAs), built using real-world data, can reduce uncertainties arising from single-arm studies. This review compared 7 case studies of regulatory and HTA agencies' evaluations of oncology ECAs.

METHODS

Food and Drug Administration multidisciplinary reviews for oncology submissions from 2014 to 2021 were screened to identify 7 cases (2 blinatumomab indications, avelumab, and erdafitinib, entrectinib, trastuzumab deruxtecan, and idecabtagene vicleucel) with ECAs to support efficacy claims. Regulatory (Food and Drug Administration, European Medicines Agency, Health Canada) and HTA (pan-Canadian Oncology Drug Review, National Institute for Health and Care Excellence, Federal Joint Committee, Haute Autorité de Santé, and Pharmaceutical Benefits Advisory Committee) submissions for these cases were reviewed. The decision makers' ECA critiques and the level of influence on the decision were analyzed and categorized.

RESULTS

Across case studies, selection bias and confounding were the most common ECA critiques. Nevertheless, agreement in critiques between and among regulators and HTA bodies was low. ECA influence on agencies' decisions also varied.

CONCLUSIONS

Evaluating the same ECA evidence, agencies focused on methodologic issues (ie, selection bias and confounding), but were often not aligned on their critiques. Further research is needed to fully characterize how agencies evaluate ECAs. This study is a first step in critically evaluating agencies' critiques of ECAs and highlights the need for future guidance development around ECA design and generation.

Access to and affordability of CAR T-cell therapy in multiple myeloma: an EBMT position paper

Chimeric antigen receptor (CAR) T-cell therapy is a promising immunotherapeutic approach in the treatment of multiple myeloma, and the recent approval of the first two CAR T-cell products could result in improved outcomes. However, it remains a complex and expensive technology, which poses challenges to health-care systems and society in general, especially in times of crises. This potentially accelerates pre-existing inequalities as access to CAR T-cell therapy varies, both between countries, depending on the level of economic development, and within countries, due to structural disparities in access to quality health care-a parameter strongly correlated with socioeconomic status, ethnicity, and lifestyle. Here, we identify two important issues: affordability and access to CAR T-cell treatment. This consensus statement from clinical investigators, clinicians, nurses, and patients from the European Society for Blood and Marrow Transplantation (EBMT) proposes solutions as part of an innovative collaborative strategy to make CAR T-cell therapy accessible to all patients with multiple myeloma.

Advancing Pharmacogenomics from Single-Gene to Preemptive Testing

Pharmacogenomic testing can be an effective tool to enhance medication safety and efficacy. Pharmacogenomically actionable medications are widely used, and approximately 90-95% of individuals have an actionable genotype for at least one pharmacogene. For pharmacogenomic testing to have the greatest impact on medication safety and clinical care, genetic information should be made available at the time of prescribing (preemptive testing). However, the use of preemptive pharmacogenomic testing is associated with some logistical concerns, such as consistent reimbursement, processes for reporting preemptive results over an individual's lifetime, and result portability. Lessons can be learned from institutions that have implemented preemptive pharmacogenomic testing. In this review, we discuss the rationale and best practices for implementing pharmacogenomics preemptively.

Clinico-Genomic Characterization of Patients with Metastatic Urothelial Carcinoma in Real-World Practice Identifies a Novel Bladder Immune Performance Index (BIPI)

PURPOSE

This retrospective analysis of the largest available clinico-genomic database used de-identified patient-level electronic health record-derived real-world data (RWD) combined with FoundationOne® comprehensive genomic profiling (CGP) to characterize patients with metastatic urothelial carcinoma (mUC) treated in the real-world setting, detect potential biomarkers, and develop a bladder immune performance index (BIPI).

EXPERIMENTAL DESIGN

Patients with mUC who started front-line single-agent immune checkpoint inhibitors (ICIs) and an unmatched group treated with front-line platinum-based chemotherapy between January 1, 2011 and September 30, 2019 were selected. Clinical and genomic data were correlated with overall survival (OS). A novel BIPI predicting outcome with ICIs was developed using machine learning methods and validated using data from a phase II trial (NCT02951767).

RESULTS

In ICI-treated patients (n=118), high tumor mutational burden (≥10 mutations/megabase) was associated with improved OS (HR 0.58 [95% CI, 0.35-0.95]; P=0.03). In chemotherapy-treated patients (n=268), those with high APOBEC mutational signature had worse OS (HR 1.43 [95% CI, 1.06-1.94]; P=0.02). Neither FGFR3 mutations nor DNA damage-repair pathway alterations were associated with OS. A novel BIPI combining clinical and genomic variables (non-metastatic at initial diagnosis, normal or above normal albumin level at baseline, prior surgery for organ-confined disease, high TMB) identified ICI-treated patients with longest OS and was validated in an independent dataset.

CONCLUSIONS

Contemporary RWD including FoundationOne® CGP can be used to characterize outcomes in real-world patients according to biomarkers beyond PD-L1. A validated, novel clinico-genomic BIPI demonstrated satisfactory prognostic performance for OS in patients with mUC receiving front-line ICI therapy.

Correlation Between Early Endpoints and Overall Survival in Non-Small-Cell Lung Cancer: A Trial-Level Meta-Analysis

Early endpoints, such as progression-free survival (PFS), are increasingly used as surrogates for overall survival (OS) to accelerate approval of novel oncology agents. Compiling trial-level data from randomized controlled trials (RCTs) could help to develop a predictive framework to ascertain correlation trends between treatment effects for early and late endpoints. Through trial-level correlation and random-effects meta-regression analysis, we assessed the relationship between hazard ratio (HR) OS and (1) HR PFS and (2) odds ratio (OR) PFS at 4 and 6 months, stratified according to the mechanism of action of the investigational product. Using multiple source databases, we compiled a data set including 81 phase II-IV RCTs (35 drugs and 156 observations) of patients with non-small-cell lung cancer. Low-to-moderate correlations were generally observed between treatment effects for early endpoints (based on PFS) and HR OS across trials of agents with different mechanisms of action. Moderate correlations were seen between treatment effects for HR PFS and HR OS across all trials, and in the programmed cell death-1/programmed cell death ligand-1 and epidermal growth factor receptor trial subsets. Although these results constitute an important step, caution is advised, as there are some limitations to our evaluation, and an additional patient-level analysis would be needed to establish true surrogacy.

Developing a Canadian Real-World Evidence Action Plan across the Drug Life Cycle

Policy makers face challenges with the number of drugs for rare indications and rapidly rising costs. In facing these challenges, decision-makers see real-world evidence (RWE) as an opportunity. Health Canada and the Canadian Agency for Drugs and Technologies in Health (CADTH) recently announced their intent to co-develop an action plan to optimize the process for the systematic use and integration of RWE into both regulatory and reimbursement decision-making in Canada. When implemented, this will have a significant impact on how drugs are approved and paid for in Canada. We highlight the key opportunities, barriers and future directions related to the use of RWE throughout the life cycle of drugs in Canada.

Emulating Control Arms for Cancer Clinical Trials Using External Cohorts Created From Electronic Health Record-Derived Real-World Data

Electronic health record (EHR)-derived real-world data (RWD) can be sourced to create external comparator cohorts to oncology clinical trials. This exploratory study assessed whether EHR-derived patient cohorts could emulate select clinical trial control arms across multiple tumor types. The impact of analytic decisions on emulation results was also evaluated. By digitizing Kaplan-Meier curves, we reconstructed published control arm results from 15 trials that supported drug approvals from January 1, 2016, to April 30, 2018. RWD cohorts were constructed using a nationwide EHR-derived de-identified database by aligning eligibility criteria and weighting to trial baseline characteristics. Trial data and RWD cohorts were compared using Kaplan-Meier and Cox proportional hazards regression models for progression-free survival (PFS) and overall survival (OS; individual cohorts) and multitumor random effects models of hazard ratios (HRs) for median endpoint correlations (across cohorts). Post hoc, the impact of specific analytic decisions on endpoints was assessed using a case study. Comparing trial data and weighted RWD cohorts, PFS results were more similar (HR range = 0.63-1.18, pooled HR = 0.84, correlation of median = 0.91) compared to OS (HR range = 0.36-1.09, pooled HR = 0.76, correlation of median = 0.85). OS HRs were more variable and trended toward worse for RWD cohorts. The post hoc case study had OS HR ranging from 0.67 (95% confidence interval (CI): 0.56-0.79) to 0.92 (95% CI: 0.78-1.09) depending on specific analytic decisions. EHR-derived RWD can emulate oncology clinical trial control arm results, although with variability. Visibility into clinical trial cohort characteristics may shape and refine analytic approaches.

EA3: A softmax algorithm for evidence appraisal aggregation

Real World Evidence (RWE) and its uses are playing a growing role in medical research and inference. Prominently, the 21st Century Cures Act—approved in 2016 by the US Congress—permits the introduction of RWE for the purpose of risk-benefit assessments of medical interventions. However, appraising the quality of RWE and determining its inferential strength are, more often than not, thorny problems, because evidence production methodologies may suffer from multiple imperfections. The problem arises to aggregate multiple appraised imperfections and perform inference with RWE. In this article, we thus develop an evidence appraisal aggregation algorithm called EA³. Our algorithm employs the softmax function—a generalisation of the logistic function to multiple dimensions—which is popular in several fields: statistics, mathematical physics and artificial intelligence. We prove that EA³ has a number of desirable properties for appraising RWE and we show how the aggregated evidence appraisals computed by EA³ can support causal inferences based on RWE within a Bayesian decision making framework. We also discuss features and limitations of our approach and how to overcome some shortcomings. We conclude with a look ahead at the use of RWE.

Validation analysis of a composite real-world mortality endpoint for patients with cancer in the United States

Objective

We expanded the previous assessment of a mortality variable suited for real‐world evidence‐focused oncology research.

Data source

We used a nationwide electronic health record (EHR)‐derived de‐identified database.

Data collection

We included patients with at least 1 of 18 cancer types between January 1, 2011 and December 31, 2017. Patient‐level structured data (EHRs, obituaries, and Social Security Death Index) and unstructured EHR data (abstracted) were linked to generate a composite mortality variable.

Study design

We benchmarked sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and ±15‐day agreement against the National Death Index (NDI). Real‐world overall survival (rwOS) was estimated using the Kaplan‐Meier method. We performed sensitivity analyses using a smaller patient cohort that underwent next‐generation sequencing testing.

Principal findings

Compared with the NDI across 18 cancer types (overall N = 160 436): sensitivity, 83.9%‐91.5% (17/18 cancer types had sensitivity ≥85.0%); specificity, 93.5%‐99.7%; PPV, 96.3%‐98.3%; NPV, 75.0%‐98.7%; ±15‐day agreement, 95.6%‐97.6%; and median rwOS estimates ranging from 2.8% to 12.7% greater. Sensitivity analysis results (n = 17 540) were consistent with the main analysis.

Conclusions

Across all cancer types analyzed, this composite mortality variable showed high sensitivity, specificity, PPV, NPV, and ±15‐day agreement, and yielded median rwOS values modestly overestimated when compared to NDI‐based results.

Real-World Experience on Omalizumab Treatment for Patients with Normocomplementemic Urticarial Vasculitis

Background

Urticarial vasculitis is a small vessel vasculitis characterized by long-lasting wheals. It was suggested omalizumab is well tolerated and effective in patients with hypocomplementaemic urticarial vasculitis.

Objective

To evaluate the clinical response and safety of omalizumab for treating patients with normocomplementaemic urticarial vasculitis (NUV) in real-world setting.

Methods

We collected data from a single-center. This study included patients with NUV who was received omalizumab therapy. During a 24-week study period, the clinical efficacy was evaluated by patient’s self-assessment instrument urticarial vasculitis activity score and Dermatology Life Quality Index.

Results

Five patients with NUV were enrolled. Three patients received 6 doses of 150 or 300 mg omalizumab subcutaneously every 4 weeks. At 24-week follow-up, it was revealed improvement of clinical manifestations and reduction of urticarial vasculitis activity score and Dermatology Life Quality Index. At 24-week visit, mild wheals recurred in one patient who was only administrated with omalizumab for 4 times. One patient did not response to omalizumab therapy. No adverse events were recorded in the 5 patients.

Conclusion

Omalizumab may be a potential choice in the treatment of patients with NUV in the real-world life.

Harnessing Real-World Evidence for the Development of Novel Cancer Therapies

Resourcing real-world evidence (RWE) is becoming an increasingly important asset in developing novel therapies for cancer. In this article, an overview of the benefits and challenges of using these data is provided. Through several case examples we highlight future applications and potential.

Ethics of Pharma Clinical Trials in the Era of Precision Oncology

Pharmaceutical industry clinical trials are ethically problematic: human research subjects are being used as a means to the end of demonstrating statistically significant efficacy of novel anticancer agents to achieve regulatory registration and marketing approval. Randomized controlled trial design is inequitable since control arm patients are denied access to the postulated best treatment. Most pharma studies do not provide clinically meaningful benefit of increased overall survival and enhanced quality of life (QOL) to cohorts and are not reliably generalizable to real-world patients. Precision oncology now enables prospective identification of patients expressing a specific cancer biomarker to determine their particular eligibility for evaluation of efficiency of molecular-targeted treatments. A patient-centered approach, collecting prospective real-world data in large populations, could provide real-world evidence of cost-effective, sustained clinical benefits of survival and QOL, while preserving the ethical beneficent compact between patient and doctor.

A multi-stakeholder approach in optimising patients' needs in the benefit assessment process of new metastatic breast cancer treatments

There is a growing understanding as science evolves that different cancer types require different approaches to treatment evaluation, especially in the metastatic stages. The introduction of new metastatic breast cancer (MBC) treatments may be hindered by several elements, including the availability of relevant evidence related to disease-specific outcomes, the benefit assessment process around the evaluation of the clinical benefit and the patients' need of new treatments. The Steering Committee (SC) found that not all issues relevant to MBC patients are consistently considered in the current benefit assessment process of new treatments. Among these are overall survival, time-to-event endpoints (e.g. progression-free survival), patients' priorities, burden of disease, MBC-specific quality of life, value in delaying chemotherapy, route of administration, side effects and toxicities, treatment adherence and the benefit of real-world evidence. This paper calls on decision makers to (1) Include MBC-specific patient priorities and outcomes in the overall benefit assessments of new MBC treatments; (2) Enhance multi-stakeholder collaboration in order to improve MBC patient outcomes.