Using oncology real-world evidence for quality improvement and discovery: the case for ASCO's CancerLinQ

Improving Diagnosis and Care for Patients With Sarcoma: Do Real-World General Practitioners Data and Prospective Data Collections Have a Place Next to Clinical Trials?

There has been growing interest in the use of real-world data (RWD) to address clinically and policy-relevant (research) questions that cannot be answered with data from randomized controlled trials (RCTs) alone. This is, for example, the case in rare malignancies such as sarcomas as limited patient numbers pose challenges in conducting RCTs within feasible timeliness, a manageable number of collaborators, and statistical power. This narrative review explores the potential of RWD to generate real-world evidence (RWE) in sarcoma research, elucidating its application across different phases of the patient journey, from prediagnosis to the follow-up/survivorship phase. For instance, examining electronic health records (EHRs) from general practitioners (GPs) enables the exploration of consultation frequency and presenting symptoms in primary care before a sarcoma diagnosis. In addition, alternative study designs that integrate RWD with well-designed observational RCTs may offer relevant information on the effectiveness of clinical treatments. As, especially in cases of ultrarare sarcomas, it can be an extreme challenge to perform well-powered randomized prospective studies. Therefore, it is crucial to support the adaptation of novel study designs. Regarding the follow-up/survivorship phase, examining EHR from primary and secondary care can provide valuable insights into identifying the short- and long-term effects of treatment over an extended follow-up period. The utilization of RWD also comes with several challenges, including issues related to data quality and privacy, as described in this study. Notwithstanding these challenges, this study underscores the potential of RWD to bridge, at least partially, gaps between evidence and practice and holds promise in contributing to the improvement of sarcoma care.

Use of Novel National Data Sets to Monitor Chemotherapy Use and Outcomes: A Retrospective Cohort Study of Non-Small-Cell Lung Cancer in Aotearoa New Zealand

PURPOSE

Te Aho o Te Kahu, the New Zealand Cancer Control Agency, is establishing a systemic anticancer therapy (SACT) database (Anti-Cancer Therapy-Nationally Organized Workstream [ACT-NOW]) which can be linked to other national health data collections. In this article, we explore the application of ACT-NOW data in the monitoring of uptake and outcomes after the public funding of pemetrexed in Aotearoa New Zealand.

METHODS

We used the ACT-NOW collection to identify patients with advanced nonsquamous non-small-cell lung cancer, who were treated with first-line platinum-based doublet chemotherapy over an 8-year period. Data were extracted for a period of 4 years before and 4 years after the national funding of pemetrexed (November 1, 2017). Treatments were classified as historical platinum doublet (cisplatin or carboplatin with gemcitabine, vinorelbine, paclitaxel, or docetaxel) or platinum pemetrexed doublet (cisplatin or carboplatin with pemetrexed). The primary outcome was the proportion of patients receiving each treatment type, before and after November 1, 2017. To prototype linkage to outcomes data, we evaluated hospitalization and 1-year overall survival (OS) rates by treatment.

RESULTS

A total of 331 patients were included from four cancer centers. All patients (116 of 116) who were treated with first-line platinum-based doublet chemotherapy between November 2013 and November 2017 received historical platinum doublet chemotherapy. After the introduction of pemetrexed, between November 2017 and November 2021, 94% (203 of 215) were treated with platinum pemetrexed doublet chemotherapy and 6% (12 of 215) with historical platinum doublet chemotherapy. Linkage to outcomes data for 1-year OS, hospitalization rates, and lengths of stay outcome data were achievable.

CONCLUSION

The ACT-NOW data set has the potential to facilitate evaluation of the impact of national-level SACT funding decisions on prescribing practice and specific patient outcomes. Our results support the use of these data to inform resource planning and quality improvement.

Geriatric drug trials on solid tumor are scarce worldwide

Background

Conducting geriatric trials is the most feasible way to address the vast underrepresentation of older adults in clinical trials of cancer therapies. This study is a globally comprehensive examination of geriatric trials for solid tumor worldwide over the last decade.

Methods

Up-to-date information on cancer drug trials in older adults aged over 59 years from the beginning of 2012 to the end of 2021 was collected from Trialtrove and Pharmaprojects. The number of identified trials was the dependent variable and corresponding analysis was conducted from the perspective of time trend, status quo and comparisons by region and country, sponsor type and cancer type, study status and phase.

Results

A total of 292 geriatric cancer drug trials were identified, of which 287 were single-region studies, 219 were initiated by academic groups, and 55 (18.8%) were terminated. Decreasing trends in the annual number of all trials (-9.2% per year) and the annual number of trials by academic groups (-9.4%) were observed over time. Of the geriatric trials, 183 were conducted in Asia; this number was significantly higher than that in Europe (74), North America (37), Oceania (4), and South America (1). Similar difference was found in participation rate in trials by academic groups ranging from 71.7% in Asia to 0.5% in South America. Of the trials, 19 and 97 were initiated before drug and indication approval, respectively, and the remaining 176 were initiated after indication approval. Phase II trials accounted for the highest proportion of trials (213, 72.9%), while phase I trials accounted for the lowest proportion (14, 4.8%). Trials by academic groups had a higher termination rate (21.5% vs. 11.0%) and fewer were phase IV trials (8.2% vs. 21.9%). Treatment was explored for 16 different cancers, with lung, colorectal and breast cancers being the most common.

Conclusion

Geriatric trials of solid tumor drugs are scarce and partially prematurely terminated. Moreover, the number of geriatric trials has decreased and differs according to region. Global guidance and regulatory supervision are needed to facilitate the acquisition of adequate evidence on drug risk-benefit profiles in older adults, and thus to achieve high-quality care and safe medication.

Cardio oncology: Digital innovations, precision medicine and health equity

The rapid emergence of cardio-oncology has resulted in a rapid growth of cardio-oncology programs, dedicated professional societies sections and committees, and multiple collaborative networks that emerged to amplify the access to care in this new subspecialty. However, most existing data, position statements and guidelines are limited by the lack of availability of large clinical trials to support these recommendations. Furthermore, there are significant challenges regarding proper access to cardio-oncology care and treatment, particularly in marginalized and minority populations. The emergence and evolution of personalized medicine, artificial intelligence (AI), and machine learning in medicine and in cardio-oncology provides an opportunity for a more targeted, personalized approach to cardiovascular complications of cancer treatment. The proper implementation of these new modalities may facilitate a more equitable approach to adequate and universal access to cardio-oncology care, improve health related outcomes, and enable health care systems to eliminate the digital divide. This article reviews and analyzes the current status on these important issues.

Pembrolizumab-combination therapy for previously untreated metastatic nonsquamous NSCLC: Real-world outcomes at US oncology practices

Objectives

The availability of immunotherapies has expanded the options for treating metastatic NSCLC, but information is needed regarding outcomes of immunotherapy for patients treated outside of clinical trials. The aim of this retrospective study was to evaluate the outcomes of therapy with first-line pembrolizumab plus pemetrexed and carboplatin (pembrolizumab-combination) for patients with metastatic nonsquamous NSCLC in the real-world setting of oncology clinics in the United States (US).

Methods

Using deidentified, longitudinal patient records from a nationwide, electronic health record-derived US database, we identified patients with metastatic nonsquamous NSCLC, without EGFR/ALK/ROS1 genomic alterations, who had received no previous systemic anticancer therapy. Eligible patients had an Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1 and initiated first-line pembrolizumab-combination therapy from 11-May-2017 to 31-January-2019; data cutoff was 31-August-2020. Patients treated in a clinical trial were excluded. Manual chart review supplemented technology-enabled abstraction to identify disease progression and tumor response. Time-to-event endpoints from initiation of pembrolizumab-combination therapy were determined using Kaplan-Meier.

Results

Of 377 patients with metastatic nonsquamous NSCLC, 105 (28%), 104 (28%), and 103 (27%) had programmed death-ligand 1 (PD-L1) expression ≥50%, 1–49%, and <1%, respectively; PD-L1 expression was not documented for 65 patients (17%). Median age was 66 years, and 227 patients (60%) were men. Median follow-up time from first-line therapy initiation to data cutoff was 31.2 months (range, 19.0-39.6 months). Median pembrolizumab real-world time on treatment (rwToT) was 5.8 months (95% CI, 5.0-6.7); 12- and 24-month on-treatment rates for pembrolizumab were 28.0% and 14.9%, respectively. Median overall survival (OS) was 17.2 months (95% CI, 13.6-19.9). For patients in PD-L1 expression ≥50%, 1-49%, <1%, and unknown cohorts, the 12-month survival rates were 66.0%, 58.5%, 54.5%, and 58.3%, respectively, and 24-month survival rates were 43.1%, 37.2%, 35.6%, and 42.0%, respectively. Median real-world progression-free survival was 6.2 months (95% CI, 5.5-7.1); and the real-world response rate was 39.3%, with median duration of response of 13.1 months (95% CI, 10.5-16.8).

Conclusions

These findings demonstrate the benefits of first-line pembrolizumab-combination therapy for patients with EGFR/ALK-wild-type, metastatic nonsquamous NSCLC and good performance status who are treated at US community oncology clinics.

First-Line Pembrolizumab Monotherapy for Advanced NSCLC With Programmed Death-Ligand 1 Expression Greater Than or Equal to 50%: Real-World Study Including Older Patients in Japan

Introduction

Pembrolizumab became available in Japan in February 2017 for first-line monotherapy of unresectable advanced and metastatic NSCLC with programmed death-ligand 1 (PD-L1) tumor proportion score (TPS) greater than or equal to 50%. This retrospective chart review study aimed to describe real-world clinical outcomes of first-line pembrolizumab monotherapy, including for patients 75 years or older, who are under-represented in clinical trials.

Methods

We identified patients (≥20 y old) at 23 sites initiating first-line pembrolizumab monotherapy from July 1, 2017, to December 20, 2018, for stages IIIB, IIIC, and IV NSCLC with PD-L1 TPS greater than or equal to 50% and Eastern Cooperative Oncology Group performance status of 0 to 2 or unknown. Patients with actionable genomic alterations (EGFR, ALK, ROS1, BRAF) and clinical trial participants were excluded. Time-to-event outcomes were estimated using Kaplan-Meier, with data cutoff on September 30, 2019.

Results

Of 441 eligible patients (78% men), 303 (69%) were younger than 75 years and 138 (31%) were 75 years or older; median age was 70 years. With median follow-up of 13.5 months, median overall survival (OS) was not reached (NR); 12- and 24-month OS rates were 72% and 58%, respectively. For ages younger than 75 and 75 years or older, median OS was NR and 23.5 months (95% confidence interval: 16.2–NR), respectively; 12-month OS rates were 74% and 67% and 24-month OS rates were 62% and 48%, respectively. Median real-world progression-free survival was similar in the two age groups (10.1 and 9.5 mo, respectively), as was median real-world time on treatment with pembrolizumab (5.7 and 5.6 mo).

Conclusions

These findings complement clinical trial results, adding real-world evidence supporting benefits of first-line pembrolizumab monotherapy for advanced NSCLC with PD-L1 TPS greater than or equal to 50%, including for patients 75 years or older.

Prioritizing Measures that Matter Within a Person-Centered Oncology Learning Health System

Background

Despite progress in developing learning health systems (LHS) and associated metrics of success, a gap remains in identifying measures to guide the implementation and assessment of the impact of an oncology LHS. Our aim was to identify a balanced set of measures to guide a person-centered oncology LHS.

Methods

A modified Delphi process and clinical value compass framework were used to prioritize measures for tracking LHS performance. A multidisciplinary group of 77 stakeholders, including people with cancer and family members, participated in 3 rounds of online voting followed by 50-minute discussions. Participants rated metrics on perceived importance to the LHS and discussed priorities.

Results

Voting was completed by 94% of participants and prioritized 22 measures within 8 domains. Patient and caregiver factors included clinical health (Eastern Cooperative Oncology Group Performance Status, survival by cancer type and stage), functional health and quality of life (Patient Reported Outcomes Measurement Information System [PROMIS] Global-10, Distress Thermometer, Modified Caregiver Strain Index), experience of care (advance care planning, collaboRATE, PROMIS Self-Efficacy Scale, access to care, experience of care, end-of-life quality measures), and cost and resource use (avoidance and delay in accessing care and medications, financial hardship, total cost of care). Contextual factors included team well-being (Well-being Index; voluntary staff turnover); learning culture (Improvement Readiness, compliance with Commission on Cancer quality of care measures); scholarly engagement and productivity (institutional commitment and support for research, academic productivity index); and diversity, equity, inclusion, and belonging (screening and follow-up for social determinants of health, inclusivity of staff and patients).

Conclusions

The person-centered LHS value compass provides a balanced set of measures that oncology practices can use to monitor and evaluate improvement across multiple domains.

Long-Term Real-World Outcomes of First-Line Pembrolizumab Monotherapy for Metastatic Non-Small Cell Lung Cancer With ≥50% Expression of Programmed Cell Death-Ligand 1

Objectives

Immune checkpoint inhibitors (ICIs) of programmed cell death 1/programmed cell death ligand 1 (PD-1/PD-L1) have been rapidly adopted in US clinical practice for first-line therapy of metastatic non-small cell lung cancer (NSCLC) since regulatory approval in October 2016, and a better understanding is needed of long-term outcomes of ICI therapy administered in real-world settings outside of clinical trials. Our aim was to describe long-term outcomes of first-line pembrolizumab monotherapy at US oncology practices for patients with metastatic NSCLC, PD-L1 expression ≥50%, and good performance status.

Methods

This retrospective two-cohort study used technology-enabled abstraction of deidentified electronic health records (EHR cohort) plus enhanced manual chart review (spotlight cohort) to study adult patients with stage IV NSCLC, PD-L1 expression ≥50%, no documented EGFR/ALK/ROS1 genomic aberration, and ECOG performance status 0-1 who initiated first-line pembrolizumab monotherapy from 1-November-2016 to 31-March-2020 (EHR cohort, with data cutoff 31-March-2021) or from 1-December-2016 to 30-November-2017 (spotlight cohort, with data cutoff 31-August-2020). Kaplan-Meier analysis was used to determine overall survival (OS; both cohorts) and, for the spotlight cohort, real-world progression-free survival (rwPFS) and real-world tumor response (rwTR).

Results

The EHR cohort included 566 patients (298 [53%] men); the spotlight cohort included 228 (105 [46%] men); median age in both cohorts was 71. Median follow-up from pembrolizumab initiation to data cutoff was 35.1 months (range, 12.0-52.7) and 38.4 months (range, 33.1-44.9) in EHR and spotlight cohorts, respectively. Median OS was 19.6 months (95% CI, 16.6-24.3) and 21.1 months (95% CI, 16.2-28.9), respectively; 3-year OS rates were 36.2% and 38.2% in EHR and spotlight cohorts, respectively. In the spotlight cohort, median rwPFS was 7.3 months (95% CI, 5.7-9.2); 88 patients (38.6%; 95% CI, 32.2-45.2) experienced rwTR of complete or partial response. For 151/228 patients (66%) who discontinued pembrolizumab, the most common reasons were disease progression (70 [46%]) and therapy-related adverse effects (35 [23%]).

Conclusions

Real-world outcomes remain consistent with outcomes observed in clinical trials, supporting long-term benefits of first-line pembrolizumab monotherapy for patients with metastatic NSCLC, PD-L1 expression ≥50%, and good performance status.

Real-World Time on Treatment with First-Line Pembrolizumab Monotherapy for Advanced NSCLC with PD-L1 Expression ≥ 50%: 3-Year Follow-Up Data

Simple Summary

Lung cancer is the leading cause of cancer-related death in the United States (US), and real-world studies are needed to understand effectiveness of cancer therapies for patients treated outside of cancer clinical trials. Pembrolizumab, an immunotherapy agent that aids the body’s immune system in fighting cancer, is administered for up to 2 years when treating advanced non-small cell lung cancer (NSCLC). We evaluated the real-world time on treatment (rwToT), a surrogate indicator that has been associated with survival in NSCLC studies, for over 1000 patients with advanced NSCLC treated initially with pembrolizumab at US oncology clinics. The median rwToT for patients with good performance status (similar to those in clinical trials) was 7.4 months, consistent with the median treatment duration in the KEYNOTE-024 trial (7.9 months). Our findings suggest long-term benefit of first-line pembrolizumab for patients with advanced NSCLC and good performance status at the start of therapy who are treated in real-world settings.

Abstract

Our aim was to evaluate real-world time on treatment (rwToT), overall and by KRAS mutation status, with first-line pembrolizumab monotherapy for advanced non-small cell lung cancer (NSCLC) in real-world oncology practice in the US. rwToT is a readily available, intermediate-range endpoint that is moderately to highly correlated with overall survival in clinical trials and real-world data. Using deidentified electronic medical record data, we studied patients with ECOG performance status (PS) of 0–2 who initiated pembrolizumab (1 November 2016 to 31 March 2020) for advanced NSCLC with programmed death-ligand 1 (PD-L1) expression ≥ 50% and without EGFR/ALK/ROS1 genomic alterations. The data cutoff was 31 March 2021, and the median study follow-up was 34 months. The Kaplan–Meier median rwToT with first-line pembrolizumab monotherapy was 7.4 months (95% CI, 6.3–8.1) for 807 patients with PS 0–1, which was consistent with the median treatment duration in the KEYNOTE-024 trial (7.9 months). The median rwToT for 237 patients with PS 2 was 2.1 months (95% CI, 1.4–2.8). For those with KRAS-mutated and KRAS wild-type nonsquamous NSCLC and PS 0–1, the median rwToT was 7.6 months and 7.0 months, respectively. Our findings suggest long-term benefit of first-line pembrolizumab monotherapy for advanced NSCLC with PD-L1 expression ≥ 50% in real-world settings in the US, particularly for patients with good performance status at the start of therapy, irrespective of KRAS status.

Learning health systems: A review of key topic areas and bibliometric trends

INTRODUCTION

The emergent field of learning health systems (LHSs) has been rapidly evolving as the concept continues to be embraced by researchers, managers, and clinicians. This paper reports on a scoping review and bibliometric analysis of the LHS literature to identify key topic areas and examine the influence and spread of recent research.

METHODS

We conducted a scoping review of LHS literature published between January 2016 and May 2020. The authors extracted publication data (eg, journal, country, authors, citation count, keywords) and reviewed full-texts to identify: type of study (empirical, non-empirical, or review), degree of focus (general or specific), and the reference used when defining LHSs.

RESULTS

A total of 272 publications were included in this review. Almost two thirds (65.1%) of the included articles were non-empirical and over two-thirds (68.4%) were from authors in the United States. More than half of the publications focused on specific areas, for example: oncology, cardiovascular care, and genomic medicine. Other key topic areas included: ethics, research, quality improvement, and electronic health records. We identified that definitions of the LHS concept are converging; however, many papers focused on data platforms and analytical processes rather than organisational and behavioural factors to support change and learning activities.

CONCLUSIONS

The literature on LHSs remains largely theoretical with definitions of LHSs focusing on technical processes to reuse data collected during the clinical process and embedding analysed data back into the system. A shift in the literature to empirical LHS studies with consideration of organisational and human factors is warranted.

Summary of the 12 Most Common Cancers in the CancerLinQ Discovery (CLQD) Database

PURPOSE

In 2014, the ASCO developed CancerLinQ (CLQ), a health technology platform for oncology. The CLQ Discovery (CLQD) database was created to make data available for research and this paper provides a summary of this database.

METHODS

This study described the clinical and demographic characteristics of the 12 most common cancers in the CLQD database. We included patients with a new malignant tumor diagnosis between January 1, 2013, and December 31, 2018, of the following cancers: breast, lung and bronchus, prostate, colon and rectum, melanoma of the skin, bladder, non-Hodgkin lymphoma, kidney and renal pelvis, uterus, leukemia, pancreas, and thyroid. Patients with an in-situ diagnosis were excluded. Summary statistics and Kaplan-Meier survival estimates were calculated for each tumor.

RESULTS

From 2013 to 2018, 491,360 patients were diagnosed with the study tumors. Breast cancer (139,506) was the most common, followed by lung and bronchus (70,959), prostate (63,303), and colon and rectum (53,504). The median age at diagnosis (years) was 61, 68, 68, and 64 in breast, lung and bronchus, prostate, and colon and rectum cohorts, respectively. Compared to the SEER 5-year overall survival estimates for several tumor types were higher in the CLQD database, possibly because of incomplete mortality capture in electronic health records.

CONCLUSION

This paper presents the first description of the CLQD database since its inception. CLQ will continue to evolve over time, and the breadth and depth of this data asset will continue to grow. ASCO and CLQ's long-term goal is to improve the quality of patient care and create a sustainable database for oncology researchers. These results demonstrate that CLQ built a scalable database that can be used for oncology research.

Real-world effectiveness of pembrolizumab in advanced melanoma: analysis of a French national clinicobiological database

Aim: To describe real-world pembrolizumab administration and outcomes for advanced melanoma in France. Materials & methods: Using the MelBase longitudinal database, this multicenter historical-prospective study examined treatment and outcomes of patients with nonuveal, unresectable stage III/IV melanoma initiating pembrolizumab from April 2016 to September 2017, with follow-up to September 2019. Kaplan-Meier time-to-event analyses were conducted. Results: Of 223 patients (median age 67; 51% men), 134 (60%), 36 (16%) and 53 (24%) initiated pembrolizumab in first-, second- and third-line, respectively. Median overall survival (months) was 32.6 (95% CI: 20.3-not reached [NR]), 14.4 (8.6-NR) and 9.3 (6.4-NR), respectively. Best real-world tumor response of complete or partial response was recorded for 49, 39 and 26% of patients, respectively. Conclusion: Study results support benefits of pembrolizumab therapy for advanced melanoma.

KMDATA: a curated database of reconstructed individual patient-level data from 153 oncology clinical trials

We created a database of reconstructed patient-level data from published clinical trials that includes multiple time-to-event outcomes such as overall survival and progression-free survival. Outcomes were extracted from Kaplan–Meier (KM) curves reported in 153 oncology Phase III clinical trial publications identified through a PubMed search of clinical trials in breast, lung, prostate and colorectal cancer, published between 2014 and 2016. For each trial that met our search criteria, we curated study-level information and digitized all reported KM curves with the software Digitizelt. We then used the digitized KM survival curves to estimate (possibly censored) patient-level time-to-event outcomes. Collections of time-to-event datasets from completed trials can be used to support the choice of appropriate trial designs for future clinical studies. Patient-level data allow investigators to tailor clinical trial designs to diseases and classes of treatments. Patient-level data also allow investigators to estimate the operating characteristics (e.g. power and type I error rate) of candidate statistical designs and methods.

Database URL: https://10.6084/m9.figshare.14642247.v1

Systemic therapy, survival and end-of-life costs for metastatic triple-negative breast cancer: retrospective SEER-Medicare study of women age ≥65 years

Aim: To analyze therapy for metastatic triple-negative breast cancer (mTNBC), factors contributing to survival and costs. Patients & methods: Using 2010-2016 SEER-Medicare data, we identified women (≥65 years) with mTNBC. Results: Of 302 eligible patients, 152 (50%) received systemic therapy. In multivariable regression analyses, only age <75 years was associated with therapy receipt (odds ratio: 2.91; 95% CI: 1.79-4.74); and only systemic therapy significantly reduced risk of death (hazard ratio: 0.34; 95% CI: 0.26-0.44). Median overall survival was 13.4 (95% CI: 11.3-15.1) vs 3.3 months (95% CI: 2.7-3.9) in therapy vs no-therapy cohorts. Mean per-patient-per-month costs <30 days before end-of-life/follow-up were $14,100 and $15,600 (2019 USD), respectively. Conclusion: Poor outcomes and high costs indicate need for more effective mTNBC therapy.

Early triple-negative breast cancer in women aged ≥65: retrospective study of outcomes, resource use and costs, 2010-2016

Aim: To examine real-world treatment patterns and outcomes in neoadjuvant and adjuvant settings for early-stage triple-negative breast cancer (TNBC). Patients & methods: Using the Surveillance, Epidemiology, and End Results-Medicare database, we identified patients (≥65 years) with newly diagnosed stage II/III TNBC in 2010-2015 who had surgery plus neoadjuvant and/or adjuvant (systemic and/or radiation) therapy. Treatment, survival, healthcare resource use and costs were assessed through 2016. Results: Of 1569 patients (>99% women), 6%/74%/20% received neoadjuvant-only/adjuvant-only/both (neo + adj) therapies, respectively. Median overall survival was 23 months/not reached (NR)/78 months, with longer survival at stage II (NR/NR/78 months) than stage III (22/43/38 months). Mean per patient per month costs were $10,620 and $17,872 in neoadjuvant and adjuvant periods. Conclusion: These findings provide insights into clinical and economic outcomes for early-stage TNBC in 2010-2016.

Older adult participation in cancer clinical trials: A systematic review of barriers and interventions

Cancer is a disease of aging and, as the world's population ages, the number of older persons with cancer is increasing and will make up a growing share of the oncology population in virtually every country. Despite this, older patients remain vastly underrepresented in research that sets the standards for cancer treatments. Consequently, most of what we know about cancer therapeutics is based on clinical trials conducted in younger, healthier patients, and effective strategies to improve clinical trial participation of older adults with cancer remain sparse. For this systematic review, the authors evaluated published studies regarding barriers to participation and interventions to improve participation of older adults in cancer trials. The quality of the available evidence was low and, despite a literature describing multifaceted barriers, only one intervention study aimed to increase enrollment of older adults in trials. The findings starkly amplify the paucity of evidence-based, effective strategies to improve participation of this underrepresented population in cancer trials. Within these limitations, the authors provide their opinion on how the current cancer research infrastructure must be modified to accommodate the needs of older patients. Several underused solutions are offered to expand clinical trials to include older adults with cancer. However, as currently constructed, these recommendations alone will not solve the evidence gap in geriatric oncology, and efforts are needed to meet older and frail adults where they are by expanding clinical trials designed specifically for this population and leveraging real-world data.

Benefits and limitations of real-world evidence: lessons from EGFR mutation-positive non-small-cell lung cancer

While randomized controlled trials (RCTs) are the gold standard for evidence-based medicine, they do not always reflect real-world patient populations, limiting their generalizability and external validity. Real-world evidence (RWE), generated during routine clinical practice, is increasingly important in determining effectiveness outside of the tightly controlled conditions of RCTs, and is now recognized by regulatory bodies as a valuable complement to RCTs. Consequently, it is increasingly important for physicians to understand how RWE data can be used alongside clinical trial data. Here, we discuss the different types of real-world observational studies, outline the benefits and limitations of RWE, and, using examples from EGFR mutation-positive non-small-cell lung cancer, outline how RWE can be used to help inform treatment decisions.

The future is now? Clinical and translational aspects of "Omics" technologies

Big data has become a central part of medical research, as well as modern life generally. "Omics" technologies include genomics, proteomics, microbiomics and increasingly other omics. These have been driven by rapid advances in laboratory techniques and equipment. Crucially, improved information handling capabilities have allowed concepts such as artificial intelligence and machine learning to enter the research world. The COVID-19 pandemic has shown how quickly information can be generated and analyzed using such approaches, but also showed its limitations. This review will look at how "omics" has begun to be translated into clinical practice. While there appears almost limitless potential in using big data for "precision" or "personalized" medicine, the reality is that this remains largely aspirational. Oncology is the only field of medicine that is widely adopting such technologies, and even in this field uptake is irregular. There are practical and ethical reasons for this lack of translation of increasingly affordable techniques into the clinic. Undoubtedly, there will be increasing use of large data sets from traditional (e.g. tumor samples, patient genomics) and nontraditional (e.g. smartphone) sources. It is perhaps the greatest challenge of the health-care sector over the coming decade to integrate these resources in an effective, practical and ethical way.

Improving Cancer Data Interoperability: The Promise of the Minimal Common Oncology Data Elements (mCODE) Initiative

PURPOSE

Because of expanding interoperability requirements, structured patient data are increasingly available in electronic health records. Many oncology data elements (eg, staging, biomarkers, documentation of adverse events and cancer outcomes) remain challenging. The Minimal Common Oncology Data Elements (mCODE) project is a consensus data standard created to facilitate transmission of data of patients with cancer.

METHODS

In 2018, mCODE was developed through a work group convened by ASCO, including oncologists, informaticians, researchers, and experts in terminologies and standards. The mCODE specification is organized by 6 high-level domains: patient, laboratory/vital, disease, genomics, treatment, and outcome. In total, 23 mCODE profiles are composed of 90 data elements.

RESULTS

A conceptual model was published for public comment in January 2019 and, after additional refinement, the first public version of the mCODE (version 0.9.1) Fast Healthcare Interoperability Resources (FHIR) implementation guide (IG) was presented at the ASCO Annual Meeting in June 2019. The specification was approved for balloting by Health Level 7 International (HL7) in August 2019. mCODE passed the HL7 ballot in September 2019 with 86.5% approval. The mCODE IG authors worked with HL7 reviewers to resolve all negative comments, leading to a modest expansion in the number of data elements and tighter alignment with FHIR and other HL7 conventions. The mCODE version 1.0 FHIR IG Standard for Trial Use was formally published on March 18, 2020.

CONCLUSION

The mCODE project has the potential to offer tremendous benefits to cancer care delivery and research by creating an infrastructure to better share patient data. mCODE is available free from www.mCODEinitiative.org. Pilot implementations are underway, and a robust community of stakeholders has been assembled across the oncology ecosystem.

Maintenance rituximab in Veterans with follicular lymphoma

Real-world practice patterns and clinical outcomes in patients with follicular lymphoma (FL), including the adoption of maintenance rituximab (MR) therapy in the United States (US), have been reported in few studies since the release of the National LymphoCare Study almost a decade ago. We analyzed data from the largest integrated healthcare system in the United States, the Veterans Health Administration (VHA), to identify rates of adoption and effectiveness of MR in FL patients after first-line (1L) treatment. We identified previously untreated patients with FL in the VHA between 2006 and 2014 who achieved at least stable disease after chemoimmunotherapy or immunotherapy. Among these patients, those who initiated MR within 238 days of 1L composed the MR group, whereas those who did not were classified as the non-MR group. We examined the effect of MR on progression-free survival (PFS) and overall survival (OS). A total of 676 patients met our inclusion criteria, of whom 300 received MR. MR was associated with significant PFS (hazard ratio [HR]=0.55, P < .001) and OS (HR = 0.53, P = .005) compared to the non-MR group, after adjusting by age, sex, ethnicity, geographic region, diagnosis period, stage, grade at diagnosis, hemoglobin, lactate dehydrogenase (LDH), Charlson comorbidity index (CCI), 1L treatment regimen, and response to 1L treatment. These results suggest that in FL patients who do not experience disease progression after 1L treatment in real-world settings, MR is associated with a significant improvement in both PFS and OS. Maintenance therapy should be considered in FL patients who successfully complete and respond to 1L therapy.

Development of CancerLinQ, a Health Information Learning Platform From Multiple Electronic Health Record Systems to Support Improved Quality of Care

PURPOSE

ASCO, through its wholly owned subsidiary, CancerLinQ LLC, developed CancerLinQ, a learning health system for oncology. A learning health system is important for oncology patients because less than 5% of patients with cancer enroll in clinical trials, leaving evidence gaps for patient populations not enrolled in trials. In addition, clinical trial populations often differ from the overall cancer population with respect to age, race, performance status, and other clinical parameters.

MATERIALS AND METHODS

Working with subscribing practices, CancerLinQ accepts data from electronic health records and transforms the local representation of a patient's care into a standardized representation on the basis of the Quality Data Model from the National Quality Forum. CancerLinQ provides this information back to the subscribing practice through a series of tools that support quality improvement. CancerLinQ also creates de-identified data sets for secondary research use.

RESULTS

As of March 2020, CancerLinQ includes data from 63 organizations across the United States that use nine different electronic health records. The database includes 1,426,015 patients with a primary cancer diagnosis, of which 238,680 have had additional information abstracted from unstructured content.

CONCLUSION

As CancerLinQ continues to onboard subscribing practices, the breadth of potential applications for a learning health care system widen. Future practice-facing tools could include real-world data visualization, recommendations for treatment of patients with actionable genetic variations, and identification of patients who may be eligible for clinical trials. Feeding these insights back into oncology practice ensures that we learn how to treat patients with cancer not just on the basis of the selective experience of the 5% that enroll in clinical trials, but from the real-world experience of the entire spectrum of patients with cancer in the United States.

Big Data in Cancer Research: Real-World Resources for Precision Oncology to Improve Cancer Care Delivery

In oncology, the term "big data" broadly describes the rapid acquisition and generation of massive amounts of information, typically from population cancer registries, electronic health records, or large-scale genetic sequencing studies. The challenge of using big data in cancer research lies in interdisciplinary collaboration and information processing to unify diverse data sources and provide valid analytics to harness meaningful information. This article provides an overview of how big data approaches can be applied in cancer research, and how they can be used to translate information into new ways to ultimately make informed decisions that improve cancer care and delivery.

Pembrolizumab for Previously Treated, PD-L1-expressing Advanced NSCLC: Real-world Time on Treatment and Overall Survival

BACKGROUND

Immune checkpoint inhibitors have been rapidly adopted for therapy of advanced non-small-cell lung cancer (aNSCLC) based on clinical trial findings. Our aim was to examine outcomes in United States oncology practice settings for patients prescribed pembrolizumab monotherapy for previously treated, programmed death ligand-1 (PD-L1)-expressing aNSCLC, thus clinically similar to patients in the KEYNOTE-010 trial.

PATIENTS AND METHODS

This retrospective observational study used a nationally representative database to identify adult patients with histologically confirmed aNSCLC and PD-L1 tumor proportion score (TPS) ≥ 1% previously treated with platinum-containing chemotherapy (and appropriate tyrosine kinase inhibitor if nonsquamous aNSCLC with EGFR/ALK genomic tumor aberration). Eligible patients initiated pembrolizumab monotherapy from January 1, 2016, to November 29, 2018; data cutoff was May 31, 2019. The Kaplan-Meier method was used to estimate real-world time on treatment (rwToT) and overall survival (OS).

RESULTS

The 349 eligible patients included 199 (57%) men; the median age was 68 years (range, 37-84 years); 70 (25%) of 278 patients with known performance status had Eastern Cooperative Oncology Group score ≥ 2. The median patient follow-up was 8.1 months (range, 1 day to 39.2 months). The median rwToT was 4.9 months (95% confidence interval [CI], 3.7-5.8 months) overall and 5.8 months (95% CI, 4.2-6.6 months) for the TPS ≥ 50% cohort (n = 218). The median OS was 13.8 months (95% CI, 11.0-16.5 months) and 16.5 months (95% CI, 13.7-22.0 months) overall and for TPS ≥ 50%, respectively; 12-month survival rates were 54% and 60%, respectively.

CONCLUSION

Patients treated at oncology practices with pembrolizumab monotherapy for previously treated PD-L1-expressing aNSCLC experienced rwToT and OS similar to treatment duration and OS in phase III clinical trial settings.

Strengthening pharma's contract with society: the value of trusted partnerships between pharma and healthcare facilitated by real-world data

This White Paper is authored by 11 industry real-world evidence (RWE) experts, with support from IQVIA, as part of the ‘RWE Leadership Forum’: a group of industry leaders who come together as noncompetitive partners to understand and respond to internal or external RWD/E challenges and opportunities with a single expert voice. Herein we aim to clarify the rules of engagement between pharma and healthcare in order to establish trust-based partnerships, which will unlock unique value for society, including the medical community and the ultimate beneficiary, the patient.

Outcomes of first-line pembrolizumab monotherapy for PD-L1-positive (TPS ≥50%) metastatic NSCLC at US oncology practices

Aim: To determine real-world outcomes with first-line pembrolizumab monotherapy for metastatic non-small-cell lung cancer with PD-L1 tumor expression ≥50%. Methods: This retrospective study included adults with ECOG 0-1 initiating first-line pembrolizumab monotherapy on/after 24 October 2016 (EHR cohort) or from 1 December 2016 through 30 November 2017 (spotlight cohort) with ≥6-month follow-up. We estimated Kaplan-Meier overall survival (OS, both cohorts), and, for spotlight, real-world progression-free survival (rwPFS) by Kaplan-Meier and real-world tumor response (rwTR). Results: For 423 patients in the EHR cohort and 188 in spotlight, median OS was 18.9 months (95% CI: 14.9-25.5) and 19.1 months (12.6-not reached), respectively. For spotlight, median rwPFS was 6.8 months (5.3-8.1); rwTR of complete/partial response was 48% (41-56%). Conclusion: Observed OS, rwPFS and rwTR were consistent with clinical trial findings.

Digital transformation in healthcare - architectures of present and future information technologies

Healthcare providers all over the world are faced with a single challenge: the need to improve patient outcomes while containing costs. Drivers include an increasing demand for chronic disease management for an aging population, technological advancements and empowered patients taking control of their health experience. The digital transformation in healthcare, through the creation of a rich health data foundation and integration of technologies like the Internet of Things (IoT), advanced analytics, Machine Learning (ML) and Artificial Intelligence (AI), is recognized as a key component to tackle these challenges. It can lead to improvements in diagnostics, prevention and patient therapy, ultimately empowering care givers to use an evidence-based approach to improve clinical decisions. Real-time interactions allow a physician to monitor a patient 'live', instead of interactions once every few weeks. Operational intelligence ensures efficient utilization of healthcare resources and services provided, thereby optimizing costs. However, procedure-based payments, legacy systems, disparate data sources with the limited adoption of data standards, technical debt, data security and privacy concerns impede the efficient usage of health information to maximize value creation for all healthcare stakeholders. This has led to a highly-regulated, constrained industry. Ultimately, the goal is to improve quality of life and saving people's lives through the creation of the intelligent healthcare provider, fully enabled to deliver value-based healthcare and a seamless patient experience. Information technologies that enable this goal must be extensible, safe, reliable and affordable, and tailored to the digitalization maturity-level of the individual organization.

Differential impact of cognitive computing augmented by real world evidence on novice and expert oncologists

INTRODUCTION

Cognitive computing point-of-care decision support tools which ingest patient attributes from electronic health records and display treatment options based on expert training and medical literature, supplemented by real world evidence (RWE), might prove useful to expert and novice oncologists. The concordance of augmented intelligence systems with best medical practices and potential influences on physician behavior remain unknown.

METHODS

Electronic health records from 88 breast cancer patients evaluated at a USA tertiary care center were presented to subspecialist experts and oncologists focusing on other disease states with and without reviewing the IBM Watson for Oncology with Cota RWE platform.

RESULTS

The cognitive computing "recommended" option was concordant with selection by breast cancer experts in 78.5% and "for consideration" option was selected in 9.4%, yielding agreements in 87.9%. Fifty-nine percent of non-concordant responses were generated from 8% of cases. In the Cota observational database 69.3% of matched controls were treated with "recommended," 11.4% "for consideration", and 19.3% "not recommended." Without guidance from Watson for Oncology (WfO)/Cota RWE, novice oncologists chose 75.5% recommended/for consideration treatments which improved to 95.3% with WfO/Cota RWE. The novices were more likely than experts to choose a non-recommended option (P < .01) without WfO/Cota RWE and changed decisions in 39% cases.

CONCLUSIONS

Watson for Oncology with Cota RWE options were largely concordant with disease expert judged best oncology practices, and was able to improve treatment decisions among breast cancer novices. The observation that nearly a fifth of patients with similar disease characteristics received non-recommended options in a real world database highlights a need for decision support.

Technology-Enabled Clinical Trials

The complexity and costs associated with traditional randomized, controlled trials have increased exponentially over time, and now threaten to stifle the development of new drugs and devices. Nevertheless, the growing use of electronic health records, mobile applications, and wearable devices offers significant promise for transforming clinical trials, making them more pragmatic and efficient. However, many challenges must be overcome before these innovations can be implemented routinely in randomized, controlled trial operations. In October of 2018, a diverse stakeholder group convened in Washington, DC, to examine how electronic health record, mobile, and wearable technologies could be applied to clinical trials. The group specifically examined how these technologies might streamline the execution of clinical trial components, delineated innovative trial designs facilitated by technological developments, identified barriers to implementation, and determined the optimal frameworks needed for regulatory oversight. The group concluded that the application of novel technologies to clinical trials provided enormous potential, yet these changes needed to be iterative and facilitated by continuous learning and pilot studies.

Next-Generation Sequencing and the Clinical Oncology Workflow: Data Challenges, Proposed Solutions, and a Call to Action

PURPOSE

Next-generation sequencing (NGS) of tumor and germline DNA is foundational for precision oncology, with rapidly expanding diagnostic, prognostic, and therapeutic implications. Although few question the importance of NGS in modern oncology care, the process of gathering primary molecular data, integrating it into electronic health records, and optimally using it as part of a clinical workflow remains far from seamless. Numerous challenges persist around data standards and interoperability, and clinicians frequently face difficulties in managing the growing amount of genomic knowledge required to care for patients and keep up to date.

METHODS

This review provides a descriptive analysis of genomic data workflows for NGS data in clinical oncology and issues that arise from the inconsistent use of standards for sharing data across systems. Potential solutions are described.

RESULTS

NGS technology, especially for somatic genomics, is well established and widely used in routine patient care, quality measurement, and research. Available genomic knowledge bases play an evolving role in patient management but lack harmonization with one another. Questions about their provenance and timeliness of updating remain. Potentially useful standards for sharing genomic data, such as HL7 FHIR and mCODE, remain primarily in the research and/or development stage. Nonetheless, their impact will likely be seen as uptake increases across care settings and laboratories. The specific use case of ASCO CancerLinQ, as a clinicogenomic database, is discussed.

CONCLUSION

Because the electronic health records of today seem ill suited for managing genomic data, other solutions are required, including universal data standards and applications that use application programming interfaces, along with a commitment on the part of sequencing laboratories to consistently provide structured genomic data for clinical use.

Real-world experience with pembrolizumab in patients with advanced melanoma: A large retrospective observational study

Pembrolizumab has been approved in the United States for treating advanced melanoma for >4 years. We examined real-world pembrolizumab use and associated outcomes in US oncology clinical practices, including patients who would not be eligible for clinical trials.Flatiron Health longitudinal database was used to identify adult patients with advanced melanoma initiating ≥1 dose of pembrolizumab from September 4, 2014, through December 31, 2016, with follow-up through December 31, 2017. Patients in any clinical trial during the study period were excluded. Overall survival (OS) and time on treatment from pembrolizumab initiation were analyzed using the Kaplan-Meier (KM) method. Subgroup analyses were conducted to examine OS for several patient characteristics including Eastern Cooperative Oncology Group (ECOG) performance status >1, brain metastases, and corticosteroids before pembrolizumab initiation.Pembrolizumab was administered to 315 (59%), 152 (29%), and 65 (12%) patients as first-, second-, and third-line/later therapy. Median age at pembrolizumab initiation was 68 years (range, 18-84); most patients were male (66%) and white (94%). Of those with available data, 38% had BRAF-mutant melanoma, 21% had elevated lactate dehydrogenase (LDH) level, and 23% had ECOG >1. Overall, 18% had brain metastases, and 23% were prescribed corticosteroids <3 months before initiating pembrolizumab. Median study follow-up was 12.9 months (range, 0.03-39.6). Median OS was 21.8 months (95% confidence interval [CI] 16.8-29.1); KM 1-year and 2-year survival rates were 61% and 48%, respectively; and median time on pembrolizumab treatment was 4.9 months (95% CI 3.7-5.5). Median OS for first-line pembrolizumab was not reached, and for second-line and third-line/later was 13.9 and 12.5 months, respectively (log-rank P = .0095). Significantly better OS (all P ≤.0014, log-rank test) was evident for patients with ECOG performance status (PS) of 0 to 1 (vs >1), normal (vs elevated) LDH level, and no (vs yes) corticosteroid prescription <3 months before. No difference was recorded in OS by brain metastases (log-rank P = .22) or BRAF mutation status (log-rank P = .90).These findings support effectiveness of pembrolizumab in the real-world clinical setting and provide important insights into patient characteristics and outcomes associated with pembrolizumab therapy for a heterogeneous patient population with advanced melanoma, including patients who would not be eligible for clinical trials.

First-line pembrolizumab monotherapy for metastatic PD-L1-positive NSCLC: real-world analysis of time on treatment

Aim: To determine real-world time on treatment (rwToT) with first-line pembrolizumab monotherapy for metastatic non-small-cell lung cancer (NSCLC) with programmed death ligand-1 (PD-L1) tumor proportion score (TPS) ≥50%. Methods: The Kaplan-Meier rwToT was estimated from electronic health record data for adults who initiated first-line pembrolizumab monotherapy for stage IV, PD-L1 TPS ≥50% NSCLC, with negative/unknown EGFR/ALK aberrations, and ≥6 months' follow-up until database cutoff. Results: A total of 386 patients with ECOG 0-1 had a median rwToT of 6.9 months (95% CI: 5.6-8.3) and 12-month on-treatment rate of 36.4% (31.2-41.6) versus 40.3% (32.5-47.9) and 37.6% (31.9-43.4) in KEYNOTE-024 (KN024) and KN042 (stage IV/TPS ≥50% subpopulation), respectively. The 24-month restricted-mean rwTOT (extrapolated) was 10.5 months (9.4-11.7), versus 11.0 (9.5-12.5) and 10.4 (9.3-11.5) in KN024 and KN042, respectively. Conclusion: First-line pembrolizumab monotherapy rwToT in metastatic PD-L1 TPS ≥50% NSCLC for trial-matched patients is similar to treatment duration in KN024 and KN042.

Design and Evaluation of an External Control Arm Using Prior Clinical Trials and Real-World Data

PURPOSE

We discuss designs and interpretable metrics of bias and statistical efficiency of "externally controlled" trials (ECT) and compare ECT performance to randomized and single-arm designs.

EXPERIMENTAL DESIGN

We specify an ECT design that leverages information from real-world data (RWD) and prior clinical trials to reduce bias associated with interstudy variations of the enrolled populations. We then used a collection of clinical studies in glioblastoma (GBM) and RWD from patients treated with the current standard of care to evaluate ECTs. Validation is based on a "leave one out" scheme, with iterative selection of a single-arm from one of the studies, for which we estimate treatment effects using the remaining studies as external control. This produces interpretable and robust estimates on ECT bias and type I errors.

RESULTS

We developed a model-free approach to evaluate ECTs based on collections of clinical trials and RWD. For GBM, we verified that inflated false positive error rates of standard single-arm trials can be considerably reduced (up to 30%) by using external control data.

CONCLUSIONS

The use of ECT designs in GBM, with adjustments for the clinical profiles of the enrolled patients, should be preferred to single-arm studies with fixed efficacy thresholds extracted from published results on the current standard of care.

The opportunities and shortcomings of using big data and national databases for sarcoma research

The rarity and heterogeneity of sarcomas make performing appropriately powered studies challenging and magnify the significance of large databases in sarcoma research. Established large tumor registries and population-based databases have become increasingly relevant for answering clinical questions regarding sarcoma incidence, treatment patterns, and outcomes. However, the validity of large databases has been questioned and scrutinized because of the inaccuracy and wide variability of coding practices and the absence of clinically relevant variables. In addition, the utilization of large databases for the study of rare cancers such as sarcoma may be particularly challenging because of the known limitations of administrative data and poor overall data quality. Currently, there are several large national cancer databases, including the Surveillance, Epidemiology, and End Results database, the National Cancer Data Base of the American College of Surgeons and the American Cancer Society, and the National Program of Cancer Registries of the Centers for Disease Control and Prevention. These databases are often used for sarcoma research, but they are limited by their dependence on administrative or billing data, the lack of agreement between chart abstractors on diagnosis codes, and the use of preexisting documented hospital diagnosis codes for tumor registries, which lead to a significant underestimation of sarcomas in large data sets. Current and future initiatives to improve databases and big data applications for sarcoma research include increasing the utilization of sarcoma-specific registries and encouraging national initiatives to expand on real-world, evidence-based data sets.

Assessment and Stratification of High-Impact Data Elements in Electronic Clinical Quality Measures: A Joint Data Quality Initiative Between CancerLinQ® and Cancer Treatment Centers of America

PURPOSE

A joint data quality initiative between the Cancer Treatment Centers of America and the ASCO big data health technology platform CancerLinQ® was initiated to document and codify the steps taken to evaluate, stratify, and determine the potential effect of data elements used for electronic clinical quality measures as captured within structured fields in electronic health records.

METHODS

The processes involved the identification of clinical concepts required in measure population criteria and then to map these to the corresponding components of the CancerLinQ data model. A quantitative assessment of mappings between electronic clinical quality measure clinical concepts and attributes from the CancerLinQ clinical database was performed. In parallel, a qualitative analysis of high-impact data elements from the Cancer Treatment Centers of America clinical measures was made using local, expert consensus.

RESULTS

An impact assessment was derived using a count of the data elements across measures and the specific population criteria affected.

CONCLUSION

A list of putative high-impact data elements can provide guidance for clinicians to facilitate specific data element capture related to quality metrics in an electronic environment.

Beyond maximum grade: modernising the assessment and reporting of adverse events in haematological malignancies

Tremendous progress in treatment and outcomes has been achieved across the whole range of haematological malignancies in the past two decades. Although cure rates for aggressive malignancies have increased, nowhere has progress been more impactful than in the management of typically incurable forms of haematological cancer. Population-based data have shown that 5-year survival for patients with chronic myelogenous and chronic lymphocytic leukaemia, indolent B-cell lymphomas, and multiple myeloma has improved markedly. This improvement is a result of substantial changes in disease management strategies in these malignancies. Several haematological malignancies are now chronic diseases that are treated with continuously administered therapies that have unique side-effects over time. In this Commission, an international panel of clinicians, clinical investigators, methodologists, regulators, and patient advocates representing a broad range of academic and clinical cancer expertise examine adverse events in haematological malignancies. The issues pertaining to assessment of adverse events examined here are relevant to a range of malignancies and have been, to date, underexplored in the context of haematology. The aim of this Commission is to improve toxicity assessment in clinical trials in haematological malignancies by critically examining the current process of adverse event assessment, highlighting the need to incorporate patient-reported outcomes, addressing issues unique to stem-cell transplantation and survivorship, appraising challenges in regulatory approval, and evaluating toxicity in real-world patients. We have identified a range of priority issues in these areas and defined potential solutions to challenges associated with adverse event assessment in the current treatment landscape of haematological malignancies.

Treatment patterns and outcomes for patients with advanced melanoma in US oncology clinical practices

AIM

To describe recent evolution in treatment patterns and outcomes for advanced melanoma (AMel).

METHODS

This retrospective observational study analyzed de-identified electronic health record data from the Flatiron Health database for 1140 adult patients who initiated first-line therapy for AMel from 1 January 2014 to 30 June 2016 with follow-up through 28 February 2017.

RESULTS

The most common first-line regimens were ipilimumab-based therapies (34%), anti-PD-1 monotherapy (26%) and BRAF/MEK inhibitor(s) (20%). First-line ipilimumab-based and BRAF inhibitor regimens decreased after the third quarter of 2014 (3Q2014), and by 2Q2016, 55 and 91% of BRAF-mutant and BRAF wild-type cohorts, respectively, received a first-line anti-PD-1 regimen. Median overall survival from first-line initiation for all patients was 18.8 months (95% CI: 16.3-23.3).

CONCLUSION

Results illustrate changing paradigms of therapy and real-world patient outcomes for AMel.

Overview of precision oncology trials: challenges and opportunities

INTRODUCTION

In recent years, the therapeutic management of selected patients with cancer has shifted toward the 'precision medicine' approach based on patient's mechanisms of tumorigenesis, and their baseline characteristics and comorbidities. Complete tumor and cell-free DNA profiling using next-generation sequencing, proteomic and RNA analysis, and immune mechanisms should to be taken into consideration and accurate bioinformatic analysis is essential to optimize patient's treatment. Areas covered: The challenges and opportunities of conducting clinical trials in precision oncology are summarized. Expert commentary: Precision medicine has significantly changed the diagnostic and therapeutic landscape of cancer. Successful implementation of precision medicine requires translational and bioinformatics infrastructure to support optimization of treatment selection. Targeted therapy, immunotherapy, T-cell therapy alone or in combination with cytotoxic or other effective therapeutic strategies and innovative clinical trials with adaptive design should be offered to all patients. Data sharing and 'N-of-1' models hold the promise to optimize the treatment of individual patients and expedite drug approval for rare alterations and tumor types. Artificial intelligence will facilitate accurate utilization of sequencing data to perform algorithm analysis. Collaboration of healthcare providers with pharmaceutical and biotechnical companies, scientific organizations, and governmental regulatory agencies have a crucial role in curing cancer.