Real-world Overall Survival Using Oncology Electronic Health Record Data: Friends of Cancer Research Pilot

Real-World Application of a Quantitative Systems Pharmacology (QSP) Model to Predict Potassium Concentrations from Electronic Health Records: A Pilot Case towards Prescribing Monitoring of Spironolactone

Quantitative systems pharmacology (QSP) models are rarely applied prospectively for decision-making in clinical practice. We therefore aimed to operationalize a QSP model for potas-sium homeostasis to predict potassium trajectories based on spironolactone administrations. For this purpose, we proposed a general workflow that was applied to electronic health records (EHR) from patients treated in a German tertiary care hospital. The workflow steps included model exploration, local and global sensitivity analyses (SA), identifiability analysis (IA) of model parameters, and specification of their inter-individual variability (IIV). Patient covariates, selected parameters, and IIV then defined prior information for the Bayesian a posteriori prediction of individual potassium trajectories of the following day. Following these steps, the successfully operationalized QSP model was interactively explored via a Shiny app. SA and IA yielded five influential and estimable parameters (extracellular fluid volume, hyperaldosteronism, mineral corticoid receptor abundance, potassium intake, sodium intake) for Bayesian prediction. The operationalized model was validated in nine pilot patients and showed satisfactory performance based on the (absolute) average fold error. This provides proof-of-principle for a Prescribing Monitoring of potassium concentrations in a hospital system, which could suggest preemptive clinical measures and therefore potentially avoid dangerous hyperkalemia or hypokalemia.

Re-Envisioning Electronic Health Records to Optimize Patient-Centered Cancer Care, Quality, Surveillance, and Research

Electronic health records (EHRs) are a significant advancement over paper records. However, the full potential of EHRs for improving care quality, patient outcomes, surveillance, and research in cancer care is yet to be realized. The organic evolution of EHRs has resulted in a number of unanticipated consequences including increased time spent by clinicians interfacing with the EHR for daily workflows. Patient access to clinicians and their records has been an important advancement in patient-centered care; however, this has brought to light additional gaps and challenges in EHRs meeting these needs. A significant challenge for EHR design and physician workflows is how best to meet the complex goals and priorities of various stakeholders including providers, researchers, patients, health systems, payors, and regulatory agencies. The National Cancer Policy Forum convened a 2022 workshop, "Innovations in Electronic Health Records for Oncology Care, Research and Surveillance," to address these challenges and to facilitate collaboration across all user groups with the goal of re-envisioning EHRs that will better support shared goals of improving patient outcomes and advancing cancer care and research without overburdening clinicians with administrative tasks. Here, we summarize the current EHR ecosystem as discussed at the workshop and highlight opportunities to improve EHR contributions to oncology evidence and care.

Exploring the discrepancies between clinical trials and real-world data: A small-cell lung cancer study

The potential of real-world data to inform clinical trial design and supplement control arms has gained much interest in recent years. The most common approach relies on reproducing control arm outcomes by matching real-world patient cohorts to clinical trial baseline populations. However, recent studies pointed out that there is a lack of replicability, generalisability, and consensus. In this article, we propose a novel approach that aims to explore and examine these discrepancies by concomitantly investigating the impact of selection criteria and operations on the measurements of outcomes from the patient data. We tested the approach on a dataset consisting of small-cell lung cancer patients receiving platinum-based chemotherapy regimens from a real-world data cohort (n = 223) and six clinical trial control arms (n = 1224). The results showed that the discrepancy between real-world and clinical trial data potentially depends on differences in both patient populations and operational conditions (e.g., frequency of assessments, and censoring), for which further investigation is required. Discovering and accounting for confounders, including hidden effects of differences in operations related to the treatment process and clinical trial study protocol, would potentially allow for improved translation between clinical trials and real-world data. Continued development of the method presented here to systematically explore and account for these differences could pave the way for transferring learning across clinical studies and developing mutual translation between the real-world and clinical trials to inform clinical study design.

Evaluation of Real-World Tumor Response Derived From Electronic Health Record Data Sources: A Feasibility Analysis in Patients With Metastatic Non-Small Cell Lung Cancer Treated With Chemotherapy

PURPOSE

Real-world data (RWD) holds promise for ascribing a real-world (rw) outcome to a drug intervention; however, ascertaining rw-response to treatment from RWD can be challenging. Friends of Cancer Research formed a collaboration to assess available data attributes related to rw-response across RWD sources to inform methods for capturing, defining, and evaluating rw-response.

MATERIALS AND METHODS

This retrospective noninterventional (observational) study included seven electronic health record data companies (data providers) providing summary-level deidentified data from 200 patients diagnosed with metastatic non-small cell lung cancer (mNSCLC) and treated with first-line platinum doublet chemotherapy following a common protocol. Data providers reviewed the availability and frequency of data components to assess rw-response (ie, images, radiology imaging reports, and clinician response assessments). A common protocol was used to assess and report rw-response end points, including rw-response rate (rwRR), rw-duration of response (rwDOR), and the association of rw-response with rw-overall survival (rwOS), rw-time to treatment discontinuation (rwTTD), and rw-time to next treatment (rwTTNT).

RESULTS

The availability and timing of clinician assessments was relatively consistent across data sets in contrast to images and image reports. Real-world response was analyzed using clinician response assessments (median proportion of patients evaluable, 77.5%), which had the highest consistency in the timing of assessments. Relative consistency was observed across data sets for rwRR (median 46.5%), as well as the median and directionality of rwOS, rwTTD, and rwTTNT. There was variability in rwDOR across data sets.

CONCLUSION

This collaborative effort demonstrated the feasibility of aligning disparate data sources to evaluate rw-response end points using clinician-documented responses in patients with mNSCLC. Heterogeneity exists in the availability of data components to assess response and related rw-end points, and further work is needed to inform drug effectiveness evaluation within RWD sources.

Treatment-related cardiovascular events in patients with non-small cell lung cancer: Evidence from real-world data with a competing risks approach

BACKGROUND

Understanding cancer treatment-related cardiovascular (CV) events is important for cancer care; however, comprehensive evaluation of CV events in patients with lung cancer is limited. This study aimed to assess the cumulative incidence and associated risks of various CV event types in patients with non-small cell lung cancer (NSCLC).

METHODS

A total of 7868 individuals aged 40 years and older, recently diagnosed with NSCLC (2007-2018), were assessed with data obtained from the National Cancer Center, Korea. This study included nine types of CV events. A 2-year cumulative incidence function (CIF) of CV events was estimated, with death as a competing event. The associated risks were assessed by subdistribution hazard ratio (sHR) in the Fine-Gray competing risks model.

RESULTS

CV events were observed in 7.8% of patients with NSCLC, with the most frequently observed types being atrial fibrillation and flutter (AF) (2.7%), venous thromboembolic disease (2.0%), and cerebrovascular disease (CeVD) (1.5%). Overall, all CV events were highest in the group treated with systemic therapy (CIF, 10.6%; 95% confidence interval [CI], 9.5%-11.8%), followed by those treated with surgery (CIF, 10.0%; 95% CI, 8.6%-11.6%); the incidence of AF (CIF, 5.7%; 95% CI, 4.6%-7.0%) was highest in patients treated with surgery. Individuals treated with systemic therapy were found to exhibit a higher CeVD risk than those treated with surgery (sHR, 4.12; 95% CI, 1.66-10.23). Among the patients who underwent surgery, those with lobectomy and pneumonectomy had a higher AF risk (vs. wedge resection/segmentectomy; sHR, 7.79; 95% CI, 1.87-32.42; sHR, 8.10; 95% CI, 1.60-40.89).

CONCLUSIONS

These findings revealed treatment-related CV event risks in patients with NSCLC, which suggests that the risk of AF in surgery and CeVD in systemic therapy should be paid more attention to achieve a better prognosis and improve cancer survivorship outcomes.

PLAIN LANGUAGE SUMMARY

Atrial fibrillation and flutter (AF) is the most common cardiovascular event, particularly at a high risk in patients with non-small cell lung cancer (NSCLC) undergoing surgery. Patients receiving surgery with poor performance status, diagnosed with regional stage, and undergoing lobectomy or pneumonectomy are at a high risk of AF. Systemic/radiotherapy is associated with cerebrovascular and ischemic heart disease in patients with NSCLC.

Pembrolizumab Plus Chemotherapy Per PD-L1 Stratum In Patients With Metastatic Non-Small Cell Lung Cancer: Real-World Effectiveness Versus Trial Efficacy

BACKGROUND

Clinical trial efficacy and real-world effectiveness of oncological treatments can differ. This study assessed the real-world survival outcomes of first-line pembrolizumab plus chemotherapy per PD-L1 stratum in patients with metastatic non-small cell lung cancer (mNSCLC) and compared them to clinical trial results.

PATIENTS AND METHODS

All patients with nonsquamous and squamous mNSCLC who received first-line pembrolizumab plus chemotherapy in 7 Dutch teaching hospitals between January 1, 2019 and December 31, 2021 were included. Hazard ratios (HR) with confidence intervals (95% CI) for overall survival (OS) and progression-free survival (PFS) were estimated to determine the efficacy-effectiveness gap (EE gap) between real-world and clinical trial, stratified by PD-L1 stratum.

RESULTS

The nonsquamous cohort (n = 486) consisted of 269 patients with PD-L1 < 1%, 158 with PD-L1 1% to 49%, and 59 with PD-L1 ≥ 50%. The squamous cohort (n = 117) consisted of 70 patients with PD-L1 < 1% and 47 with PD-L1 ≥ 1%. For OS, an EE gap was observed in nonsquamous patients with PD-L1 < 1% (HR 1.38 (95% CI 1.06-1.78; median OS 10 vs. 17.2 months) and HRs consistently >1 in all other nonsquamous and squamous PD-L1 strata, although not statistically significant. No EE-gap for PFS was observed in any stratum.

CONCLUSION

No significant EE gap was found for pembrolizumab plus chemotherapy, except in the stratum nonsquamous mNSCLC with <1% PD-L1 tumor expression. In these patients, the survival in real-world was considerably shorter compared to the clinical trial results. Further studies are needed to determine which patient, treatment and or context factors contribute to this disparity.

Use of Real-World Evidence in a Virtual Bridging Analysis for a Human Epidermal Growth Factor Receptor 2-Targeted Antibody-Drug Conjugate in Gastric Cancer

This study bridged pharmacokinetic, efficacy, and safety clinical trial data from Japan to a Western population using real-world evidence (RWE) to investigate the antibody-drug conjugate trastuzumab deruxtecan (T-DXd) in the treatment of human epidermal growth factor receptor 2 (HER2)-positive advanced gastric cancer. Using population pharmacokinetic and exposure-response (efficacy/safety) models, exposure-efficacy data from 117 patients and exposure-safety data from 158 patients in Japan who received T-DXd 6.4 mg/kg as second-line or later treatment were bridged to RWE including covariate information from 25 Western patients with HER2-positive gastric cancer who received second-line or later T-DXd treatment. Pharmacokinetic simulations indicated that intact T-DXd and released drug (DXd) steady-state exposures were comparable between Western patients and patients from Japan; the Western/Japan ratio of exposure medians ranged from 0.82 (T-DXd steady-state minimum concentration) to 1.18 (DXd steady-state maximum concentration). Exposure-efficacy simulations estimated a confirmed objective response rate of 28.6% (90% confidence interval, 20.8-38.4) in real-world Western patients versus 40.1% (90% confidence interval, 33.5-47.0) in patients from Japan, possibly because of checkpoint inhibitor use in 4% versus 30% of patients, respectively. Western patients had a higher estimated rate of serious adverse events than patients from Japan (42.2% vs 34.6%); however, the rate of interstitial lung disease was lower (less than 10%) in Western patients. Overall, T-DXd was predicted to have meaningful clinical activity and a manageable safety profile in Western patients with HER2-positive gastric cancer. Using RWE, bridging analysis supported US approval of T-DXd 6.4 mg/kg in advanced gastric cancer before a clinical trial was completed in Western patients.

Improving Real-World Mortality Data Quality in Oncology Research: Augmenting Electronic Medical Records With Obituary, Social Security Death Index, and Commercial Claims Data

PURPOSE

This study evaluated the relative improvements in mortality data capture of adding different external data to enriched electronic medical records (EMRs) for patients with melanoma.

METHODS

An enriched EMR database, containing structured and unstructured data, was used to evaluate the incremental mortality data capture of the following external data sources: Social Security Administration (SSA), public obituary, and an administrative open-claims database for the claims data set. Overall survival (OS) was assessed for each data set and the composite data set using the Kaplan-Meier method.

RESULTS

A total of 3,882 patients were included in the study. The enriched EMR data set identified 1,085 patients with a death record. The SSA data set identified 213 patients (73 unique when combined with enriched EMR) with a death record, while the obituary data set identified 1,127 patients (241 unique). The administrative claims data set identified 378 patients (73 unique) with a death record; however, all these unique patients were already accounted for in the combined SSA and obituary data set. The composite data set yielded a median OS of 13.39 years, about 4 years shorter than the enriched EMR data set alone (17.63 years).

CONCLUSION

When the enriched EMR data set was augmented with one external data set, the obituary data set provided the most additional value, followed by claims, and then SSA. The augmentation of all the data sources had a significant impact on the OS results compared with enriched EMR alone.

Real-world data for precision cancer medicine-A European perspective

Leveraging real-world data (RWD) for drug access is necessary to overcome a key challenge of modern precision oncology: tackling numerous low-prevalence oncogenic mutations across cancers. Withholding a potentially active medication in patients with rare mutations for the sake of control chemotherapy or "best" supportive care is neither practicable nor ethically justifiable anymore, particularly as RWD could meanwhile be used instead, according to scientific principles outlined by the US Food and Drug Administration, European Medicines Agency and other stakeholders. However, practical implementation varies, with occasionally opposite recommendations based on the same evidence in different countries. In the face of growing need for precision drugs, more transparency of evaluation, a priori availability of guidance for the academia and industry, as well as a harmonized framework for health technology assessment across the European Union (EU) are imperative. These could in turn trigger infrastructural changes in national and pan-European registries, cancer management guidelines (e.g., frequency of routine radiologic restaging, inclusion of patient-reported outcomes), and the health data space, to ensure conformity with declared standards and facilitate extraction of RWD sets (including patient-level data) suitable for approval and pricing with minimal effort. For an EU-wide unification of precision cancer medicine, collective negotiation of drug supply contracts and funding solidarity would additionally be required to handle the financial burden. According to experience from pivotal European programs, off-label use could potentially also be harmonized across EU-states to accelerate availability of novel drugs, streamline collection of valuable RWD, and mitigate related costs through wider partnerships with pharmaceutical companies.

Treatment patterns and overall survival of patients with double-class and triple-class refractory multiple myeloma: a US electronic health record database study

Patients with relapsed/refractory multiple myeloma (RRMM) resistant to multiple drug classes remain a high unmet need population. This longitudinal retrospective cohort study assessed real-world treatment patterns and outcomes in adults with RRMM. Patients who had three or more prior lines of therapy including a proteasome inhibitor (PI) and an immunomodulatory agent (double-exposed) were further categorized as refractory to a PI and an immunomodulatory agent (double-class refractory, n = 381) or additionally to an anti-CD38 monoclonal antibody (triple-class refractory, n = 173). Treatment options are limited for patients with double-class or triple-class refractory disease. Retreatment is a part of standard of care. Bortezomib and lenalidomide had the highest retreatment rates among double-class and triple-class refractory patients. Survival outcomes remain poor among RRMM patients with median overall survival (OS) of 22.3 and 11.6 months for double-class refractory and triple-class refractory patients, respectively. This study highlights the need for novel efficacious therapies in this heavily pretreated RRMM population.

A novel analytical framework for risk stratification of real-world data using machine learning: A small cell lung cancer study

In recent studies, small cell lung cancer (SCLC) treatment guidelines based on Veterans' Administration Lung Study Group limited/extensive disease staging and resulted in broad and inseparable prognostic subgroups. Evidence suggests that the eight versions of tumor, node, and metastasis (TNM) staging can play an important role to address this issue. The aim of the present study was to improve the detection of prognostic subgroups from a real-word data (RWD) cohort of patients and analyze their patterns using a development pipeline with thoracic oncologists and machine learning methods. The method detected subgroups of patients informing unsupervised learning (partition around medoids) including the impact of covariates on prognosis (Cox regression and random survival forest). An analysis was carried out using patients with SCLC (n = 636) with stage IIIA-IVB according to TNM classification. The analysis yielded k = 7 compacted and well-separated clusters of patients. Performance status (Eastern Cooperative Oncology Group-Performance Status), lactate dehydrogenase, spreading of metastasis, cancer stage, and CRP were the baselines that characterized the subgroups. The selected clustering method outperformed standard clustering techniques, which were not capable of detecting meaningful subgroups. From the analysis of cluster treatment decisions, we showed the potential of future RWD applications to understand disease, develop individualized therapies, and improve healthcare decision making.

A review of stakeholder recommendations for defining fit-for-purpose real-world evidence algorithms

Aim: The credibility and value of real-world evidence (RWE) are either supported or undermined by the algorithms (i.e., operational definitions) used. Methods: We conducted a targeted evidence review of key RWE decision makers' published recommendations on RWE algorithms through April 2021. Stakeholders were regulatory bodies, other governmental agencies and payer organizations. Results: Our review identified recommended criteria: relevance, validity, reliability, responsiveness, transparency and replicability, safety, feasibility and quality process. Stakeholders routinely recommended accuracy measures, subgroups evaluation and specific considerations for assessing exposures and covariates and the underlying real-world data (RWD) quality. Conclusion: The importance of stakeholder guidance on fit-for-purpose RWE algorithms is growing. We highlight gaps that future guidance and stakeholder recommendations could address.

R WE ready for reimbursement? A round up of developments in real-world evidence relating to HTA: part 5

In the latest update we focus on recent publications which have provided insights into the importance of focusing on the development and consideration of a body of real-world evidence, and an approach to evaluating the complex area of treatment sequencing.