The Integration of Clinical Trials With the Practice of Medicine: Repairing a House Divided.

Importance: Optimal health care delivery, both now and in the future, requires a continuous loop of knowledge generation, dissemination, and uptake on how best to provide care, not just determining what interventions work but also how best to ensure they are provided to those who need them. The randomized clinical trial (RCT) is the most rigorous instrument to determine what works in health care. However, major issues with both the clinical trials enterprise and the lack of integration of clinical trials with health care delivery compromise medicine's ability to best serve society. Observations: In most resource-rich countries, the clinical trials and health care delivery enterprises function as separate entities, with siloed goals, infrastructure, and incentives. Consequently, RCTs are often poorly relevant and responsive to the needs of patients and those responsible for care delivery. At the same time, health care delivery systems are often disengaged from clinical trials and fail to rapidly incorporate knowledge generated from RCTs into practice. Though longstanding, these issues are more pressing given the lessons learned from the COVID-19 pandemic, heightened awareness of the disproportionate impact of poor access to optimal care on vulnerable populations, and the unprecedented opportunity for improvement offered by the digital revolution in health care. Four major areas must be improved. First, especially in the US, greater clarity is required to ensure appropriate regulation and oversight of implementation science, quality improvement, embedded clinical trials, and learning health systems. Second, greater adoption is required of study designs that improve statistical and logistical efficiency and lower the burden on participants and clinicians, allowing trials to be smarter, safer, and faster. Third, RCTs could be considerably more responsive and efficient if they were better integrated with electronic health records. However, this advance first requires greater adoption of standards and processes designed to ensure health data are adequately reliable and accurate and capable of being transferred responsibly and efficiently across platforms and organizations. Fourth, tackling the problems described above requires alignment of stakeholders in the clinical trials and health care delivery enterprises through financial and nonfinancial incentives, which could be enabled by new legislation. Solutions exist for each of these problems, and there are examples of success for each, but there is a failure to implement at adequate scale. Conclusions and Relevance: The gulf between current care and that which could be delivered has arguably never been wider. A key contributor is that the 2 limbs of knowledge generation and implementation-the clinical trials and health care delivery enterprises-operate as a house divided. Better integration of these 2 worlds is key to accelerated improvement in health care delivery.

Mobilizing data during a crisis: Building rapid evidence pipelines using multi-institutional real world data.

The COVID-19 pandemic generated tremendous interest in using real world data (RWD). Many consortia across the public and private sectors formed in 2020 with the goal of rapidly producing high-quality evidence from RWD to guide medical decision-making, public health priorities, and more. Experiences were gathered from five large consortia on rapid multi-institutional evidence generation during the COVID-19 pandemic. Insights have been compiled across five dimensions: consortium composition, governance structure and alignment of priorities, data sharing, data analysis, and evidence dissemination. The purpose of this piece is to offer guidance on building large-scale multi-institutional RWD analysis pipelines for future public health issues. The composition of each consortium was largely influenced by existing collaborations. A central set of priorities for evidence generation guided each consortium, however different approaches to governance emerged. Challenges surrounding limited access to clinical data due to various contributors were overcome in unique ways. While all consortia used different methods to construct and analyze patient cohorts ranging from centralized to federated approaches, all proved effective for generating meaningful real-world evidence. Actionable recommendations for clinical practice and public health agencies were made from translating insights from consortium analyses. Each consortium was successful in rapidly answering questions about COVID-19 diagnosis and treatment despite all taking slightly different approaches to data sharing and analysis. Leveraging RWD, leveraged in a manner that applies scientific rigor and transparency, can complement higher-level evidence and serve as an important adjunct to clinical trials to quickly guide policy and critical care, especially for a pandemic response.

Diversity, Equity, and Inclusion in Clinical Research: A Path Toward Precision Health for Everyone.

Healthcare disparities are a persistent societal problem. One of the contributing factors to this status quo is the lack of diversity and representativeness of research efforts, which result in nongeneralizable evidence that, in turn, provides suboptimal means to enable the best possible outcomes at the individual level. There are several strategies that research teams can adopt to improve the diversity, equity, and inclusion (DEI) of their efforts; these strategies span the totality of the research path, from initial design to the shepherding of clinical data through a potential regulatory process. These strategies include more intentionality and DEI-based goal-setting, more diverse research and leadership teams, better community engagement to set study goals and approaches, better tailored outreach interventions, decentralization of study procedures and incorporation of innovative technology for more flexible data collection, and self-surveillance to identify and prevent biases. Within their remit of overlooking research efforts, regulatory authorities, as stakeholders, also have the potential for a positive effect on the DEI of emerging clinical evidence. All these are implementable tools and mechanisms that can make study participation more approachable to diverse communities, and ultimately generate evidence that is more generalizable and a conduit for better outcomes. The research community has an imperative to make DEI principles key foundational aspects in study conduct in order to pursue better personalized medicine for diverse patient populations.

Leveraging the health information technology infrastructure to advance federal research priorities.

Ensuring that federally funded health research keeps pace with the explosion of health data depends on better information technology (IT), access to high-quality electronic health data, and supportive policies. Because it prominently funds and conducts health research, the U.S. federal government needs health IT to rapidly evolve and has the ability to drive that evolution. The Office of the National Coordinator for Health Information Technology developed the National Health IT Priorities for Research: A Policy and Development Agenda (the Agenda) that identifies health IT priorities for research in consultation with relevant federal agencies. This article describes support for the Agenda from the Food and Drug Administration, the National Institutes of Health, and the Veterans Health Administration. Advancing the Agenda will benefit these agencies and support their missions as well as the entire ecosystem leveraging the health IT infrastructure or using data from health IT systems for research.

Characterizing the Feasibility and Performance of Real-World Tumor Progression End Points and Their Association With Overall Survival in a Large Advanced Non-Small-Cell Lung Cancer Data Set.

PURPOSE: Large, generalizable real-world data can enhance traditional clinical trial results. The current study evaluates reliability, clinical relevance, and large-scale feasibility for a previously documented method with which to characterize cancer progression outcomes in advanced non-small-cell lung cancer from electronic health record (EHR) data. METHODS: Patients who were diagnosed with advanced non-small-cell lung cancer between January 1, 2011, and February 28, 2018, with two or more EHR-documented visits and one or more systemic therapy line initiated were identified in Flatiron Health's longitudinal EHR-derived database. After institutional review board approval, we retrospectively characterized real-world progression (rwP) dates, with a random duplicate sample to ascertain interabstractor agreement. We calculated real-world progression-free survival, real-world time to progression, real-world time to next treatment, and overall survival (OS) using the Kaplan-Meier method (index date was the date of first-line therapy initiation), and correlations between OS and other end points were assessed at the patient level (Spearman's ρ). RESULTS: Of 30,276 eligible patients,16,606 (55%) had one or more rwP event. Of these patients, 11,366 (68%) had subsequent death, treatment discontinuation, or new treatment initiation. Correlation of real-world progression-free survival with OS was moderate to high (Spearman's ρ, 0.76; 95% CI, 0.75 to 0.77; evaluable patients, n = 20,020), and for real-world time to progression correlation with OS was lower (Spearman's ρ, 0.69; 95% CI, 0.68 to 0.70; evaluable patients, n = 11,902). Interabstractor agreement on rwP occurrence was 0.94 (duplicate sample, n = 1,065) and on rwP date 0.85 (95% CI, 0.81 to 0.89; evaluable patients n = 358 [patients with two independent event captures within 30 days]). Median rwP abstraction time from individual EHRs was 18.0 minutes (interquartile range, 9.7 to 34.4 minutes). CONCLUSION: We demonstrated that rwP-based end points correlate with OS, and that rwP curation from a large, contemporary EHR data set can be reliable, clinically relevant, and feasible on a large scale.

Real-world progression, treatment, and survival outcomes during rapid adoption of immunotherapy for advanced non-small cell lung cancer.

BACKGROUND: Despite the rapid adoption of immunotherapies in advanced non-small cell lung cancer (advNSCLC), knowledge gaps remain about their real-world (rw) performance. METHODS: This retrospective, observational, multicenter analysis used the Flatiron Health deidentified electronic health record-derived database of rw patients with advNSCLC who received treatment with PD-1 and/or PD-L1 (PD-[L]1) inhibitors before July 1, 2017 (N = 5257) and had ≥6 months of follow-up. The authors investigated PD-(L)1 line of treatment and PD-L1 testing rates and the relationship between overall survival (OS) and rw intermediate endpoints: progression-free survival (rwPFS), rw time to progression (rwTTP), rw time to next treatment (rwTTNT), and rw time to discontinuation (rwTTD). RESULTS: First-line PD-(L)1 inhibitor use increased from 0% (in the third quarter of 2014 [Q3 2014]) to 42% (Q2 2017) over the study period. PD-L1 testing also increased (from 3% in Q3 2015 to 70% in Q2 2017). The estimated median OS was 9.3 months (95% CI, 8.9-9.8 months), and the estimated rwPFS was 3.2 months (95% CI, 3.1-3.3 months). Longer OS and rwPFS were associated with ≥50% PD-L1 percentage staining results. Correlations (⍴) between OS and intermediate endpoints were ⍴ = 0.75 (95% CI, 0.73-0.76) for rwPFS and ⍴ = 0.60 (95% CI, 0.57-0.63) for rwTTP, and, for treatment-based intermediate endpoints, correlations were ⍴ = 0.60 (95% CI, 0.56-0.64) for rwTTNT (N = 856) and ⍴ = 0.81 (95% CI, 0.80-0.82) for rwTTD. CONCLUSIONS: The use of first-line PD-(L)1 inhibitors and PD-L1 testing has substantially increased, with better outcomes for patients who have ≥50% PD-L1 percentage staining. Intermediate rw tumor-dynamics estimates were moderately correlated with OS in patients with advNSCLC who received immunotherapy, highlighting the need for optimizing and standardizing rw endpoints to enhance the understanding of patient outcomes outside clinical trials.

An Exploratory Analysis of Real-World End Points for Assessing Outcomes Among Immunotherapy-Treated Patients With Advanced Non-Small-Cell Lung Cancer.

PURPOSE: This pilot study examined the ability to operationalize the collection of real-world data to explore the potential use of real-world end points extracted from data from diverse health care data organizations and to assess how these relate to similar end points in clinical trials for immunotherapy-treated advanced non-small-cell lung cancer. PATIENTS AND METHODS: Researchers from six organizations followed a common protocol using data from administrative claims and electronic health records to assess real-world end points, including overall survival (rwOS), time to next treatment, time to treatment discontinuation (rwTTD), time to progression, and progression-free survival, among patients with advanced non-small-cell lung cancer treated with programmed death 1/programmed death-ligand 1 inhibitors in real-world settings. Data sets included from 269 to 6,924 patients who were treated between January 2011 and October 2017. Results from contributors were anonymized. RESULTS: Correlations between real-world intermediate end points (rwTTD and time to next treatment) and rwOS were moderate to high (range, 0.6 to 0.9). rwTTD was the most consistent end points as treatment detail was available in all data sets. rwOS at 1 year post-programmed death-ligand 1 initiation ranged from 40% to 57%. In addition, rwOS as assessed via electronic health records and claims data fell within the range of median OS values observed in relevant clinical trials. Data sources had been used extensively for research with ongoing data curation to assure accuracy and practical completeness before the initiation of this research. CONCLUSION: These findings demonstrate that real-world end points are generally consistent with each other and with outcomes observed in randomized clinical trials, which substantiates the potential validity of real-world data to support regulatory and payer decision making. Differences observed likely reflect true differences between real-world and protocol-driven practices.

A behavioral cancer pain intervention: A randomized noninferiority trial comparing in-person with videoconference delivery.

OBJECTIVE: Behavioral cancer pain interventions are efficacious for improving important pain outcomes; yet, traditional in-person delivery limits patient access. This study compared videoconference-delivered mobile health pain coping skills training (mPCST) to in-person pain coping skills training (PCST-traditional). METHODS: This study was a randomized, noninferiority trial with cancer patients. Participants (N = 178) were randomly assigned to four, 45-minute sessions of mPCST or PCST-traditional. Session content focused on evidence-based cognitive and behavioral pain management skills. Assessments were completed at baseline, posttreatment, and 3-month posttreatment, and included measures of primary intervention outcomes (ie, pain severity and pain interference) and secondary intervention outcomes (ie, physical symptoms, psychological distress, physical well-being, and self-efficacy). The main study aim tested whether mPCST was more accessible (defined as feasibility, acceptability, patient burden, and engagement) than PCST-traditional. The second aim tested whether mPCST was noninferior to PCST-traditional. RESULTS: mPCST demonstrated significantly greater feasibility (ie, attrition, adherence, and time to completion) than PCST-traditional. Both groups reported similar patient burden and engagement as well as a high degree of acceptability. All intervention outcomes demonstrated noninferiority at posttreatment and, with the exception of physical symptoms, 3-month posttreatment. Concerning the primary intervention outcomes, 95% CIs for the mean differences (d) were below the noninferiority margin of 1 for pain severity (posttreatment d = 0.09, 95% CI, -0.63-0.81; 3 months d = -0.43 95% CI, -1.22-0.36) and pain interference (posttreatment d = -0.11, 95% CI, -0.99-0.76; 3 months d = -0.26 95% CI, -1.14-0.62). CONCLUSION: mPCST is highly accessible and noninferior to PCST-traditional.

Association of Patient Characteristics and Tumor Genomics With Clinical Outcomes Among Patients With Non-Small Cell Lung Cancer Using a Clinicogenomic Database.

Importance: Data sets linking comprehensive genomic profiling (CGP) to clinical outcomes may accelerate precision medicine. Objective: To assess whether a database that combines EHR-derived clinical data with CGP can identify and extend associations in non-small cell lung cancer (NSCLC). Design, Setting, and Participants: Clinical data from EHRs were linked with CGP results for 28 998 patients from 275 US oncology practices. Among 4064 patients with NSCLC, exploratory associations between tumor genomics and patient characteristics with clinical outcomes were conducted, with data obtained between January 1, 2011, and January 1, 2018. Exposures: Tumor CGP, including presence of a driver alteration (a pathogenic or likely pathogenic alteration in a gene shown to drive tumor growth); tumor mutation burden (TMB), defined as the number of mutations per megabase; and clinical characteristics gathered from EHRs. Main Outcomes and Measures: Overall survival (OS), time receiving therapy, maximal therapy response (as documented by the treating physician in the EHR), and clinical benefit rate (fraction of patients with stable disease, partial response, or complete response) to therapy. Results: Among 4064 patients with NSCLC (median age, 66.0 years; 51.9% female), 3183 (78.3%) had a history of smoking, 3153 (77.6%) had nonsquamous cancer, and 871 (21.4%) had an alteration in EGFR, ALK, or ROS1 (701 [17.2%] with EGFR, 128 [3.1%] with ALK, and 42 [1.0%] with ROS1 alterations). There were 1946 deaths in 7 years. For patients with a driver alteration, improved OS was observed among those treated with (n = 575) vs not treated with (n = 560) targeted therapies (median, 18.6 months [95% CI, 15.2-21.7] vs 11.4 months [95% CI, 9.7-12.5] from advanced diagnosis; P < .001). TMB (in mutations/Mb) was significantly higher among smokers vs nonsmokers (8.7 [IQR, 4.4-14.8] vs 2.6 [IQR, 1.7-5.2]; P < .001) and significantly lower among patients with vs without an alteration in EGFR (3.5 [IQR, 1.76-6.1] vs 7.8 [IQR, 3.5-13.9]; P < .001), ALK (2.1 [IQR, 0.9-4.0] vs 7.0 [IQR, 3.5-13.0]; P < .001), RET (4.6 [IQR, 1.7-8.7] vs 7.0 [IQR, 2.6-13.0]; P = .004), or ROS1 (4.0 [IQR, 1.2-9.6] vs 7.0 [IQR, 2.6-13.0]; P = .03). In patients treated with anti-PD-1/PD-L1 therapies (n = 1290, 31.7%), TMB of 20 or more was significantly associated with improved OS from therapy initiation (16.8 months [95% CI, 11.6-24.9] vs 8.5 months [95% CI, 7.6-9.7]; P < .001), longer time receiving therapy (7.8 months [95% CI, 5.5-11.1] vs 3.3 months [95% CI, 2.8-3.7]; P < .001), and increased clinical benefit rate (80.7% vs 56.7%; P < .001) vs TMB less than 20. Conclusions and Relevance: Among patients with NSCLC included in a longitudinal database of clinical data linked to CGP results from routine care, exploratory analyses replicated previously described associations between clinical and genomic characteristics, between driver mutations and response to targeted therapy, and between TMB and response to immunotherapy. These findings demonstrate the feasibility of creating a clinicogenomic database derived from routine clinical experience and provide support for further research and discovery evaluating this approach in oncology.

Patient free text reporting of symptomatic adverse events in cancer clinical research using the National Cancer Institute's Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE).

OBJECTIVE: The study sought to describe patient-entered supplemental information on symptomatic adverse events (AEs) in cancer clinical research reported via a National Cancer Institute software system and examine the feasibility of mapping these entries to established terminologies. MATERIALS AND METHODS: Patients in 3 multicenter trials electronically completed surveys during cancer treatment. Each survey included a prespecified subset of items from the National Cancer Institute's Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE). Upon completion of the survey items, patients could add supplemental symptomatic AE information in a free text box. As patients typed into the box, structured dropdown terms could be selected from the PRO-CTCAE item library or Medical Dictionary for Regulatory Activities (MedDRA), or patients could type unstructured free text for submission. RESULTS: Data were pooled from 1760 participants (48% women; 78% White) who completed 8892 surveys, of which 2387 (26.8%) included supplemental symptomatic AE information. Overall, 1024 (58%) patients entered supplemental information at least once, with an average of 2.3 per patient per study. This encompassed 1474 of 8892 (16.6%) dropdowns and 913 of 8892 (10.3%) unstructured free text entries. One-third of the unstructured free text entries (32%) could be mapped post hoc to a PRO-CTCAE term and 68% to a MedDRA term. DISCUSSION: Participants frequently added supplemental information beyond study-specific survey items. Almost half selected a structured dropdown term, although many opted to submit unstructured free text entries. Most free text entries could be mapped post hoc to PRO-CTCAE or MedDRA terms, suggesting opportunities to enhance the system to perform real-time mapping for AE reporting. CONCLUSIONS: Patient reporting of symptomatic AEs using a text box functionality with mapping to existing terminologies is both feasible and informative.

Associations Between Polypharmacy, Symptom Burden, and Quality of Life in Patients with Advanced, Life-Limiting Illness.

BACKGROUND: Polypharmacy may be particularly burdensome near the end of life, as patients "accumulate" medications to treat and prevent multiple diseases. OBJECTIVE: To evaluate associations between polypharmacy, symptom burden, and quality of life (QOL) in patients with advanced, life-limiting illness (clinician-estimated, 1 month-1 year). DESIGN: Secondary analysis of baseline data from a trial of statin discontinuation. PARTICIPANTS: Adults with advanced, life-limiting illness. MAIN MEASURES: Polypharmacy was assessed by summing the number of non-statin medications taken regularly or as needed. Symptom burden was assessed using the Edmonton Symptom Assessment Scale (range 0-90; higher scores indicating greater symptom burden) and QOL was assessed using the McGill QOL Questionnaire (range 0-10; higher scores indicating better QOL). Linear regression models assessed associations between polypharmacy, symptom burden, and QOL. KEY RESULTS: Among 372 participants, 47% were age 75 or older and 35% were enrolled in hospice. The mean symptom score was 27.0 (standard deviation (SD) 16.1) and the mean QOL score was 7.0 (SD 1.3). The average number of non-statin medications was 11.6 (SD 5.0); one-third of participants took ≥ 14 medications. In adjusted models, higher polypharmacy was associated with higher symptom burden (coefficient 0.81; p < .001) and lower QOL (coefficient - .06; p = .001). Adjusting for symptom burden weakened the association between polypharmacy and QOL (coefficient - .03; p = .045) without a significant interaction, suggesting that worse quality of life associated with polypharmacy may be related to medication-associated symptoms. CONCLUSIONS: Among adults with advanced illness, taking more medications is associated with higher symptom burden and lower QOL. Attention to medication-related symptoms and shared decision-making regarding deprescribing are warranted in this setting. NIH TRIAL REGISTRY NUMBER: ClinicalTrials.gov Identifier for Parent Study - NCT01415934.