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

Analysis of the characteristics and the degree of pragmatism exhibited by pragmatic-labelled trials of antineoplastic treatments

BACKGROUND

Pragmatic clinical trials (PCTs) are designed to reflect how an investigational treatment would be applied in clinical practice. As such, unlike their explanatory counterparts, they measure therapeutic effectiveness and are capable of generating high-quality real-world evidence. However, the conduct of PCTs remains extremely rare. The scarcity of such studies has contributed to the emergence of the efficacy-effectiveness gap and has led to calls for launching more of them, including in the field of oncology. This analysis aimed to identify self-labelled pragmatic trials of antineoplastic interventions and to evaluate whether their use of this label was justified.

METHODS

We searched PubMed® and Embase® for publications corresponding with studies that investigated antitumor therapies and that were tagged as pragmatic in their titles, abstracts and/or index terms. Subsequently, we consulted all available source documents for the included trials and extracted relevant information from them. The data collected were then used to appraise the degree of pragmatism displayed by the PCTs with the help of the validated PRECIS-2 tool.

RESULTS

The literature search returned 803 unique records, of which 46 were retained upon conclusion of the screening process. This ultimately resulted in the identification of 42 distinct trials that carried the 'pragmatic' label. These studies examined eight different categories of neoplasms and were mostly randomized, open-label, multicentric, single-country trials sponsored by non-commercial parties. On a scale of one (very explanatory) to five (very pragmatic), the median PCT had a PRECIS-2 score per domain of 3.13 (interquartile range: 2.57-3.53). The most and least pragmatic studies in the sample had a score of 4.44 and 1.57, respectively. Only a minority of trials were described in sufficient detail to allow them to be graded across all domains of the PRECIS-2 instrument. Many of the studies examined also had features that arguably precluded them from being pragmatic altogether, such as being monocentric or placebo-controlled in nature.

CONCLUSION

PCTs of antineoplastic treatments are generally no more pragmatic than they are explanatory.

Defining the role of real-world data in cancer clinical research: The position of the European Organisation for Research and Treatment of Cancer

The emergence of the precision medicine paradigm in oncology has led to increasing interest in the integration of real-world data (RWD) into cancer clinical research. As sources of real-world evidence (RWE), such data could potentially help address the uncertainties that surround the adoption of novel anticancer therapies into the clinic following their investigation in clinical trials. At present, RWE-generating studies which investigate antitumour interventions seem to primarily focus on collecting and analysing observational RWD, typically forgoing the use of randomisation despite its methodological benefits. This is appropriate in situations where randomised controlled trials (RCTs) are not feasible and non-randomised RWD analyses can offer valuable insights. Nevertheless, depending on how they are designed, RCTs have the potential to produce strong and actionable RWE themselves. The choice of which methodology to employ for RWD studies should be guided by the nature of the research question they are intended to answer. Here, we attempt to define some of the questions that do not necessarily require the conduct of RCTs. Moreover, we outline the strategy of the European Organisation for Research and Treatment of Cancer (EORTC) to contribute to the generation of robust and high-quality RWE by prioritising the execution of pragmatic trials and studies set up according to the trials-within-cohorts approach. If treatment allocation cannot be left up to random chance due to practical or ethical concerns, the EORTC will consider undertaking observational RWD research based on the target trial principle. New EORTC-sponsored RCTs may also feature concurrent prospective cohorts composed of off-trial patients.

Considerations for the Utility of Real-World Evidence Beyond Trial Data in Advanced NSCLC: The Case of Frontline Tyrosine Kinase Inhibitors

Background

To extend the discussion on the use of real-world evidence (RWE) in conveying the clinical value of treatment beyond trial data, the primary objective of this study was to assess if efficacy gains in progression-free survival (PFS) observed in randomized controlled trials (RCT) correlate with efficacy gains in the real-world setting. For this, we assessed the treatment benefit of three tyrosine kinase inhibitors (TKIs) in aNSCLC.

Methods

Using matched cohorts identified in the Flatiron Health database (2011-2020), we mimicked the following cohorts of TKI versus platinum-based chemotherapy (PBC) from the following trials: (1) erlotinib, EURTAC; (2) afatinib, LUX-Lung 3; and (3) crizotinib, PROFILE 1014. Time to treatment discontinuation (TTD) hazard ratio (HR) was used as a proxy for PFS HR, the primary endpoint in the selected RCTs. HRs were calculated via Cox proportional hazard models.

Results

Overall, 1,118 patients were included across the three RWE cohorts. Frontline TKI regimens had statistically significantly better real-world TTD than their matched PBC comparator group (HR 0.37, 95% confidence interval [CI] 0.30-0.44 for erlotinib; HR 0.42, 95% CI 0.32-0.55 for afatinib; HR 0.37, 95% CI 0.26-0.53 for crizotinib). The benefit in real-world OS was not different between TKIs and PBC patients, attributed to a high proportion of switching to subsequent therapy. Study findings of relative treatment benefit (HR) for real-world TTD and OS were deemed similar to those for PFS and OS from the pivotal RCTs.

Conclusion

The relative treatment effect, measured as real-world TTD HR over the long term, was similar to trial-based PFS HR, implying that the clinical benefit of aNSCLC treatments conveyed in trials translated into the clinical setting. This is important, given that OS data interpretation is limited, even with longer follow-up. Additionally, our RWE analysis endorses TTD as a relevant endpoint to measure clinical benefit.

Health economic evidence for the use of molecular biomarker tests in hematological malignancies: A systematic review

Objectives

Molecular biomarker tests can inform the clinical management of genomic heterogeneous hematological malignancies, yet their availability in routine care largely depends on the supporting health economic evidence. This study aims to systematically review the economic evidence for recent molecular biomarker tests in hematological malignancies.

Methods

We conducted a systematic search in five electronic databases for studies published between January 2010 and October 2020. Publications were independently screened by two reviewers. Clinical study characteristics, economic methodology, and results were extracted, and reporting quality was assessed.

Results

Fourteen studies were identified, of which half (n = 7; 50%) were full economic evaluations examining both health and economic outcomes. Studies were predominantly conducted in a first‐line treatment setting (n = 7; 50%) and adopted a non‐lifetime time horizon to measure health outcomes and costs (n = 7; 50%). Five studies reported that companion diagnostics for associated therapies were likely cost‐effective for acute myeloid leukemia, chronic myeloid leukemia, diffuse large B‐cell lymphoma, and multiple myeloma. Four studies suggested molecular biomarker tests for treatment monitoring in chronic myeloid leukemia were likely cost‐saving.

Conclusions

Although there is initial confirmation of the promising health economic results, the present research for molecular biomarker tests in hematological malignancies is sparse with many applications of technological advances yet to be evaluated.

Photodynamic Therapeutic Effect of Nanostructured Metal Sulfide Photosensitizers on Cancer Treatment

Photodynamic therapy (PDT) utilizes photosensitizers (PSs) to produce reactive oxygen species (ROSs) upon irradiation, which causes the shutdown of vessels and deprives the tumor of nutrients and oxygen, and in turn induces adverse effects on the immune system. However, significant efforts are needed to increase the efficiency in PDT in terms of light delivery to specific PSs for the clinical treatment of tumors located deep under the skin. Even though PDT offers a disease site-specific treatment modality, current efforts are directed to improve the solubility (in body fluids and injectable solvents), photostability, amphiphilicity (for tissue penetration), elimination, and systemic toxicity of traditional PSs based on porphyrin derivatives. Nanostructured materials show promising features to achieve most of such combined efforts. They can be artificially engineered to carry multiple theranostic agents onto targeted tumor sites. However, recent studies on photosensitive Cd-based nanostructures, mostly used in PDT, indicate that leeching of Cd2+ ions is stimulated when they are exposed to harsh biological conditions for continuous periods of time, thus making them acutely toxic and hindering their applications in in vivo settings. Since nanostructured materials are not completely immune to degradation, great strides have been made to seek new alternatives. In this review, we focus on the latest advances of Cd-free nanostructured metal transition sulfides (MTSs) as alternative PSs and study their high-energy transfer efficiency, rational designs, and potential applications in cancer-targeted PDT. Nanostructured MTSs are discussed in the context of their versatility to serve as phototherapy agents and superior properties, including their strong absorption in the NIR region, excellent photothermal conversion efficiency, controlled reactive oxygen species (ROS) production, versatile surface chemistry, high fluorescence, and structural and thermal stability. We discuss the latest advancements in correlating the self-aggregation of MTSs with their passive tumor cell targeting, highlighting their ability to efficiently produce ROSs, and mitigating their dark toxicity through polymeric functionalization. Treatment of deep-seated tumors by using these PSs upon preferential uptake by tumor tissues (due to the enhanced permeability and retention effect) is also reviewed. We finally summarize the main future perspectives of MTSs as next-generation PSs within the context of cancer theranostics.

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.

Explainable Artificial Intelligence Reveals Novel Insight into Tumor Microenvironment Conditions Linked with Better Prognosis in Patients with Breast Cancer

We investigated the data-driven relationship between immune cell composition in the tumor microenvironment (TME) and the ≥5-year survival rates of breast cancer patients using explainable artificial intelligence (XAI) models. We acquired TCGA breast invasive carcinoma data from the cbioPortal and retrieved immune cell composition estimates from bulk RNA sequencing data from TIMER2.0 based on EPIC, CIBERSORT, TIMER, and xCell computational methods. Novel insights derived from our XAI model showed that B cells, CD8+ T cells, M0 macrophages, and NK T cells are the most critical TME features for enhanced prognosis of breast cancer patients. Our XAI model also revealed the inflection points of these critical TME features, above or below which ≥5-year survival rates improve. Subsequently, we ascertained the conditional probabilities of ≥5-year survival under specific conditions inferred from the inflection points. In particular, the XAI models revealed that the B cell fraction (relative to all cells in a sample) exceeding 0.025, M0 macrophage fraction (relative to the total immune cell content) below 0.05, and NK T cell and CD8+ T cell fractions (based on cancer type-specific arbitrary units) above 0.075 and 0.25, respectively, in the TME could enhance the ≥5-year survival in breast cancer patients. The findings could lead to accurate clinical predictions and enhanced immunotherapies, and to the design of innovative strategies to reprogram the breast TME.