Generating and using real-world data: A worthwhile uphill battle.

The precision oncology paradigm challenges the feasibility and data generalizability of traditional clinical trials. Consequently, an unmet need exists for practical approaches to test many subgroups, evaluate real-world drug value, and gather comprehensive, accessible datasets to validate novel biomarkers. Real-world data (RWD) are increasingly recognized to have the potential to fill this gap in research methodology. Established applications of RWD include informing disease epidemiology, pharmacovigilance, and healthcare quality assessment. Currently, concerns regarding RWD quality and comprehensiveness, privacy, and biases hamper their broader application. Nonetheless, RWD may play a pivotal role in supplementing clinical trials, enabling conditional reimbursement and accelerated drug access, and innovating trial conduct. Moreover, purpose-built RWD repositories may support the extension or refinement of drug indications and facilitate the discovery and validation of new biomarkers. This perspective explores the potential of leveraging RWD to advance oncology, highlights its benefits and challenges, and suggests a path forward in this evolving field.

The Master Observational Trial: A New Class of Master Protocol to Advance Precision Medicine.

This commentary introduces a new clinical trial construct, the Master Observational Trial (MOT), which hybridizes the power of molecularly based master interventional protocols with the breadth of real-world data. The MOT provides a clinical venue to allow molecular medicine to rapidly advance, answers questions that traditional interventional trials generally do not address, and seamlessly integrates with interventional trials in both diagnostic and therapeutic arenas. The result is a more comprehensive data collection ecosystem in precision medicine.

An overview of real-world data sources for oncology and considerations for research.

Generating evidence on the use, effectiveness, and safety of new cancer therapies is a priority for researchers, health care providers, payers, and regulators given the rapid pace of change in cancer diagnosis and treatments. The use of real-world data (RWD) is integral to understanding the utilization patterns and outcomes of these new treatments among patients with cancer who are treated in clinical practice and community settings. An initial step in the use of RWD is careful study design to assess the suitability of an RWD source. This pivotal process can be guided by using a conceptual model that encourages predesign conceptualization. The primary types of RWD included are electronic health records, administrative claims data, cancer registries, and specialty data providers and networks. Careful consideration of each data type is necessary because they are collected for a specific purpose, capturing a set of data elements within a certain population for that purpose, and they vary by population coverage and longitudinality. In this review, the authors provide a high-level assessment of the strengths and limitations of each data category to inform data source selection appropriate to the study question. Overall, the development and accessibility of RWD sources for cancer research are rapidly increasing, and the use of these data requires careful consideration of composition and utility to assess important questions in understanding the use and effectiveness of new therapies.

Integrating Evidence to Guide Use of Biologics and Small Molecules for Inflammatory Bowel Diseases.

Advances in science have led to the development of multiple biologics and small molecules for the treatment of inflammatory bowel diseases (IBDs). This growth in advanced medical therapies has been accompanied by an increase in methodological innovation to study and compare therapies. Guidelines provide an evidence-based approach to integrating therapies into routine practice, but they are often unable to provide timely recommendations as new therapies come to market, and they have limited incorporation of real-world evidence when making recommendations. This limits the scope and usability of guidelines, and a gap remains in defining how best to position and integrate advanced medical therapies for IBD. In this review, we provide a framework for clinicians and researchers to understand key differences in sources of evidence, how different methodologies are applied to study the comparative effectiveness of advanced medical therapies in IBD, and considerations for how these sources of evidence can be used to better integrate current guideline recommendations. Over time, we anticipate this framework will allow for a transition to living guidelines and/or practice recommendations.

Trajectories of clinical characteristics, complications and treatment choices in data-driven subgroups of type 2 diabetes.

AIMS/HYPOTHESIS: This study aimed to explore the added value of subgroups that categorise individuals with type 2 diabetes by k-means clustering for two primary care registries (the Netherlands and Scotland), inspired by Ahlqvist's novel diabetes subgroups and previously analysed by Slieker et al. METHODS: We used two Dutch and Scottish diabetes cohorts (N=3054 and 6145; median follow-up=11.2 and 12.3 years, respectively) and defined five subgroups by k-means clustering with age at baseline, BMI, HbA1c, HDL-cholesterol and C-peptide. We investigated differences between subgroups by trajectories of risk factor values (random intercept models), time to diabetes-related complications (logrank tests and Cox models) and medication patterns (multinomial logistic models). We also compared directly using the clustering indicators as predictors of progression vs the k-means discrete subgroups. Cluster consistency over follow-up was assessed. RESULTS: Subgroups' risk factors were significantly different, and these differences remained generally consistent over follow-up. Among all subgroups, individuals with severe insulin resistance faced a significantly higher risk of myocardial infarction both before (HR 1.65; 95% CI 1.40, 1.94) and after adjusting for age effect (HR 1.72; 95% CI 1.46, 2.02) compared with mild diabetes with high HDL-cholesterol. Individuals with severe insulin-deficient diabetes were most intensively treated, with more than 25% prescribed insulin at 10 years of diagnosis. For severe insulin-deficient diabetes relative to mild diabetes, the relative risks for using insulin relative to no common treatment would be expected to increase by a factor of 3.07 (95% CI 2.73, 3.44), holding other factors constant. Clustering indicators were better predictors of progression variation relative to subgroups, but prediction accuracy may improve after combining both. Clusters were consistent over 8 years with an accuracy ranging from 59% to 72%. CONCLUSIONS/INTERPRETATION: Data-driven subgroup allocations were generally consistent over follow-up and captured significant differences in risk factor trajectories, medication patterns and complication risks. Subgroups serve better as a complement rather than as a basis for compressing clustering indicators.

Trajectories of BMI before and after diagnosis of type 2 diabetes in a real-world population.

AIMS/HYPOTHESIS: Few studies have examined the clinical characteristics associated with changes in weight before and after diagnosis of type 2 diabetes. Using a large real-world cohort, we derived trajectories of BMI before and after diabetes diagnosis, and examined the clinical characteristics associated with these trajectories, including assessing the impact of pre-diagnosis weight change on post-diagnosis weight change. METHODS: We performed an observational cohort study using electronic medical records from individuals in the Scottish Care Information Diabetes Collaboration database. Two trajectories were calculated, based on observed BMI measurements between 3 years and 6 months before diagnosis and between 1 and 5 years after diagnosis. In the post-diagnosis trajectory, each BMI measurement was time-dependently adjusted for the effects of diabetes medications and HbA1c change. RESULTS: A total of 2736 individuals were included in the study. There was a pattern of pre-diagnosis weight gain, with 1944 individuals (71%) gaining weight overall, and 875 (32%) gaining more than 0.5 kg/m2 per year. This was followed by a pattern of weight loss after diagnosis, with 1722 individuals (63%) losing weight. Younger age and greater social deprivation were associated with increased weight gain before diagnosis. Pre-diagnosis weight change was unrelated to post-diagnosis weight change, but post-diagnosis weight loss was associated with older age, female sex, higher BMI, higher HbA1c and weight gain during the peri-diagnosis period. When considering the peri-diagnostic period (defined as from 6 months before to 12 months after diagnosis), we identified 986 (36%) individuals who had a high HbA1c at diagnosis but who lost weight rapidly and were most aggressively treated at 1 year; this subgroup had the best glycaemic control at 5 years. CONCLUSIONS/INTERPRETATION: Average weight increases before diagnosis and decreases after diagnosis; however, there were significant differences across the population in terms of weight changes. Younger individuals gained weight pre-diagnosis, but, in older individuals, type 2 diabetes is less associated with weight gain, consistent with other drivers for diabetes aetiology in older adults. We have identified a substantial group of individuals who have a rapid deterioration in glycaemic control, together with weight loss, around the time of diagnosis, and who subsequently stabilise, suggesting that a high HbA1c at diagnosis is not inevitably associated with a poor outcome and may be driven by reversible glucose toxicity.

Metabolic health in people living with type 1 diabetes in Belgium: a repeated cross-sectional study.

AIMS/HYPOTHESIS: Metabolic abnormalities such as central obesity, insulin resistance, dyslipidaemia and hypertension, often referred to as 'the metabolic syndrome' (or 'combined metabolic abnormalities'), are increasingly being identified in people living with type 1 diabetes, accelerating the risk for CVD. As a result, in recent years, treatment in people living with type 1 diabetes has shifted to improving overall metabolic health rather than glucose control alone. In Belgium, diabetes care for people living with type 1 diabetes is centrally organised. The Initiative for Quality Improvement and Epidemiology in Diabetes, imposed by the Belgian health insurance system, has systematically collected data from patients on intensive insulin therapy treated in all 101 diabetes clinics in Belgium since 2001. The aim of this real-world study is to describe the evolution of treatment and metabolic health, including the prevalence of obesity and combined metabolic abnormalities, in people living with type 1 diabetes over the past 20 years, and to compare the treatment and prevalence of complications between those with and without combined metabolic abnormalities. METHODS: We analysed data on adults (≥16 years old) living with type 1 diabetes, who were diagnosed at age ≤45 years and who had a diabetes duration ≥1 year, collected between 2001 and 2022. The evolution of HbA1c, BMI, LDL-cholesterol, systolic BP, lipid-lowering therapy and antihypertensive therapy over time was analysed. The prevalence of individual and multiple metabolic abnormalities according to various definitions of the metabolic syndrome/combined metabolic abnormalities was analysed, and the association between combined metabolic abnormalities and metabolic health indicators, complications and treatment was investigated in the 2022 data. RESULTS: The final dataset consisted of 26,791 registrations of adults living with type 1 diabetes collected between 2001 and 2022. Although glycaemic and lipid control generally improved over time, the prevalence of obesity strongly increased (12.1% in 2001 vs 21.7% in 2022, p<0.0001), as did the presence of combined metabolic abnormalities (WHO criteria: 26.9% in 2001 vs 42.9% in 2022 in women, p<0.0001; 30.4% in 2001 vs 52.1% in 2022 in men, p<0.0001; WHO criteria without albuminuria: 22.3% in 2001 vs 40.6% in 2022 in women, p<0.0001; 25.1% in 2001 vs 49.2% in 2022 in men, p<0.0001; NCEP-ATPIII criteria: 39.9% in 2005 vs 57.2% in 2022 in women, p<0.0001; 40.8% in 2005 vs 60.9% in 2022 in men, p<0.0001; IDF criteria: 43.9% in 2005 vs 59.3% in 2022 in women, p<0.001; 33.7% in 2005 vs 50.0% in 2022 in men, p<0.0001). People with combined metabolic abnormalities had higher glucose levels compared to those without combined metabolic abnormalities (HbA1c >58 mmol in men: 48.9% vs 36.9%; HbA1c >58 mmol in women: 53.3% vs 41.1%, p<0.0001). People with combined metabolic abnormalities were more often treated with adjunct therapies such as metformin, sodium-glucose transport protein 2 inhibitors and glucagon-like peptide-1 receptor agonists. In both men and women, the presence of combined metabolic abnormalities was strongly related to the presence of eye complications, peripheral neuropathy, chronic kidney disease and CVD, corrected for age, diabetes duration and HbA1c. CONCLUSIONS/INTERPRETATION: Overweight, obesity and combined metabolic abnormalities are increasingly being identified in people living with type 1 diabetes, further accelerating the risk of microvascular and macrovascular complications. Early identification of the presence of combined metabolic abnormalities should enable therapeutic interventions to be modified towards multifactorial approaches, with attention to education on avoidance of overweight (e.g. dietary counselling) in addition to strict glycaemic control and intensification of use of antihypertensive agents and statins. Use of adjunct therapies in this population as a tool should be explored more thoroughly to reduce risk of complications.

Management of vulnerable patients hospitalized for COVID-19 with remdesivir: a retrospective comparative effectiveness study of mortality in US hospitals.

BACKGROUND: COVID-19 remains a major public health concern, with continued resurgences of cases and substantial risk of mortality for hospitalized patients. Remdesivir has become standard-of-care for hospitalized COVID-19 patients. Given the continued evolution of the disease, clinical management relies on evidence from the current endemic period. METHODS: Using the PINC AI Healthcare database, effectiveness of remdesivir was evaluated among adults hospitalized with a primary diagnosis of COVID-19 between December 2021 and February 2024. Three cohorts were analysed: adults, elderly (≥65 years), and those with documented COVID-19 pneumonia. Analyses were stratified by oxygen requirements. Patients receiving remdesivir were matched to those not receiving remdesivir using propensity score matching. Cox proportional hazards models were used to examine in-hospital mortality. RESULTS: 169,965 adults hospitalized for COVID-19 were included, of which 94,129 (55.4%) initiated remdesivir in the first two days of hospitalization. Remdesivir was associated with a significantly lower mortality rate as compared to no remdesivir among patients with no supplemental oxygen charges (NSOc) (aHR [95% CI]: 14-day, 0.75 [0.69-0.82]; 28-day, 0.77 [0.72-0.83]) and among those with supplemental oxygen charges (SOc): 14-day, 0.76 [0.72-0.81]; 28-day, 0.79 [0.74-0.83]) (p<0.0001, for all). Similar findings were observed for elderly patients and those hospitalized with COVID-19 pneumonia. CONCLUSIONS: This evidence builds on learnings from randomized controlled trials from the pandemic era to inform clinical practices. Remdesivir was associated with significant reduction in mortality for hospitalized patients including the elderly and those with COVID-19 pneumonia.

Lower mortality risk associated with remdesivir + dexamethasone versus dexamethasone alone for the treatment of patients hospitalized for COVID-19.

BACKGROUND: Treatment guidelines were developed early in the pandemic when much about COVID-19 was unknown. Given the evolution of SARS-CoV-2, real-world data can provide clinicians with updated information. The objective of this analysis was to assess mortality risk in patients hospitalized for COVID-19 during the Omicron period receiving remdesivir+dexamethasone versus dexamethasone alone. METHODS: A large, multicenter US hospital database was used to identify hospitalized adult patients, with a primary discharge diagnosis of COVID-19 also flagged as "present on admission" treated with remdesivir+dexamethasone or dexamethasone alone from December 2021 to April 2023. Patients were matched 1:1 using propensity score matching and stratified by baseline oxygen requirements. Cox proportional hazards model was used to assess time to 14- and 28-day in-hospital all-cause mortality. RESULTS: A total of 33 037 patients were matched, with most patients ≥65 years old (72%), White (78%), and non-Hispanic (84%). Remdesivir+dexamethasone was associated with lower mortality risk versus dexamethasone alone across all baseline oxygen requirements at 14 days (no supplemental oxygen charges: adjusted hazard ratio [95% CI]: 0.79 [0.72-0.87], low flow oxygen: 0.70 [0.64-0.77], high flow oxygen/non-invasive ventilation: 0.69 [0.62-0.76], invasive mechanical ventilation/extracorporeal membrane oxygen (IMV/ECMO): 0.78 [0.64-0.94]), with similar results at 28 days. CONCLUSIONS: Remdesivir+dexamethasone was associated with a significant reduction in 14- and 28-day mortality compared to dexamethasone alone in patients hospitalized for COVID-19 across all levels of baseline respiratory support, including IMV/ECMO. However, the use of remdesivir+dexamethasone still has low clinical practice uptake. In addition, these data suggest a need to update the existing guidelines.

Remdesivir-associated survival outcomes among immunocompromised patients hospitalized for COVID-19: real-world evidence from the Omicron dominant era.

BACKGROUND: Patients with immunocompromising conditions are at an increased risk for coronavirus disease 2019 (COVID-19)-related hospitalizations and mortality. Randomized clinical trials provide limited enrollment, if any, to inform outcomes of such patients treated with remdesivir. METHODS: Using the US PINC AI Healthcare Database, we identified adult patients with immunocompromising conditions, hospitalized for COVID-19 between December 2021 and February 2024. Primary outcome was all-cause inpatient mortality examined in propensity score (PS) matched patients in remdesivir versus non-remdesivir groups. Subgroup analyses were performed for patients with cancer, hematologic malignancies, and solid organ/hematopoietic stem cell transplant recipients. RESULTS: Of 28,966 patients included in the study, 16,730 (58%) received remdesivir during first two days of hospitalization. After PS matching, 8,822 patients in remdesivir and 8,822 patients in non-remdesivir group were analyzed. Remdesivir was associated with a significantly lower mortality among patients with no supplemental oxygen (aHR [95% CI]: 14-day, 0.73 [0.62-0.86]; 28-day, 0.79 [0.68-0.91]) and among those with supplemental oxygen (14-day, 0.75 [0.67-0.85]; 28-day, 0.78 [0.70-0.86]). Remdesivir was also associated with lower mortality in subgroups of patients with cancer, hematological malignancies (including leukemia, lymphoma, and multiple myeloma), and solid organ/hematopoietic stem cell transplantation. CONCLUSIONS: In this large cohort of patients with immunocompromising conditions hospitalized for COVID-19, remdesivir was associated with significant improvement in survival, including patients with varied underlying immunocompromising conditions. The integration of current real-world evidence into clinical guideline recommendations can inform clinical communities to optimize treatment decisions in the evolving COVID-19 era, extending beyond the conclusion of the public health emergency declaration.

Public Health Benefits of Applying Evidence-Based Best Practices in Managing Patients Hospitalized for COVID-19.

BACKGROUND: As COVID-19-related mortality remains a concern, optimal management of patients hospitalized for COVID-19 continues to evolve. We developed a population model based on real-world evidence to quantify the clinical impact of increased utilization of remdesivir, the effectiveness of which has been well established in hospitalized patients with COVID-19. METHODS: The PINC AI healthcare database records for patients hospitalized for COVID-19 from January to December 2023 were stratified by those treated with or without remdesivir ("RDV" and "No RDV") and by supplemental oxygen requirements: no supplemental oxygen charges (NSOc), low-flow oxygen (LFO), and high-flow oxygen/non-invasive ventilation (HFO/NIV). Key vulnerable subgroups such as elderly and immunocompromised patients were also evaluated. The model applied previously published hazard ratios (HRs) to 28-day in-hospital mortality incidence to determine the number of potential lives saved if additional "No RDV" patients had been treated with remdesivir upon hospital admission. RESULTS: Of 84,810 hospitalizations for COVID-19 in 2023, 13,233 "No RDV" patients were similar in terms of characteristics and clinical presentation to the "RDV" patients. The model predicted that initiation of remdesivir in these patients could have saved 231 lives. Projected nationally, this translates to >800 potential lives saved (95% CI: 469-1,126). Eighty-nine percent of potential lives saved were elderly and 19% were immunocompromised individuals. Seventy-one percent were among NSOc or LFO patients. CONCLUSIONS: This public health model underscores the value of initiating remdesivir upon admission in patients hospitalized for COVID-19, in accordance with evidence-based best practices, to minimize lives lost due to SARS-CoV-2 infection.

The use of pembrolizumab monotherapy for the management of head and neck squamous cell carcinoma (HNSCC) in the UK.

Pembrolizumab has received approval in the UK as first-line monotherapy for recurrent and/or metastatic HNSCC (R/M HNSCC) following the results of the KEYNOTE-048 trial, which demonstrated a longer overall survival (OS) in comparison to the EXTREME chemotherapy regimen in patients with a combined positive score (CPS) ≥1. In this article, we provide retrospective real-world data on the role of pembrolizumab monotherapy as first-line systemic therapy for HNSCC across 18 centers in the UK from March 20, 2020 to May 31, 2021. 211 patients were included, and in the efficacy analysis, the objective response rate (ORR) was 24.7%, the median progression-free survival (PFS) was 4.8 months (95% confidence interval [CI]: 3.6-6.1), and the median OS was 10.8 months (95% CI 9.0-12.5). Pembrolizumab monotherapy was well tolerated, with 18 patients having to stop treatment owing to immune-related adverse events (irAEs). 53 patients proceeded to second-line treatment with a median PFS2 of 10.2 months (95% CI: 8.8-11.5). Moreover, patients with documented irAEs had a statistically significant longer median PFS (11.3 vs. 3.3 months; log-rank p value = <.001) and median OS (18.8 vs. 8.9 months; log-rank p value <.001). The efficacy and safety of pembrolizumab first-line monotherapy for HNSCC has been validated using real-world data.

Emulations of Oncology Trials Using Real-World Data: A Systematic Literature Review.

By evaluating published emulations of oncology RCTs studies in which both the active and comparator groups are sourced from RWD and target trial results are available for benchmarking, this systematic review aims to gain insight into factors related to emulation performance. Thirteen oncology emulation studies using various types of RWD were identified through an online database search of PubMed through 2022. Based on the ROBINS-I tool, most studies (N=8) had a serious risk of overall bias driven by risk of bias from confounding. Approximately half of the studies (N=6) fully proxied the RCT entry criteria. Of 11 RWD studies that provided sufficient detail to quantify emulation performance, the emulation HR estimate fell within the 95% CI of the trial estimate in 9 of the studies. There were no clear trends between risk of bias or degree to which the entry criteria were proxied and emulation performance. Findings may have been influenced by publication bias and researcher degrees of freedom, as only one emulation study pre-registered its protocol. Tools for comprehensively characterizing factors that affect emulation performance, including the real-world clinical context as it relates to the RCT research question, are needed to evaluate the feasibility of a RCT emulation.

Tree-based scan statistics to generate drug repurposing hypotheses: a test case using sodium-glucose cotransporter-2 inhibitors.

Most drug repurposing studies using real-world data focused on validating, instead of generating, hypotheses. We used tree-based scan statistics to generate repurposing hypotheses for sodium-glucose cotransporter-2 inhibitors (SGLT2i). We used an active-comparator, new-user design to create a 1:1 propensity-score matched cohort of SGLT2i and dipeptidyl peptidase-4 inhibitors (DPP4i) initiators in the MerativeTM MarketScan® Research Databases. Tree-based scan statistics were estimated across an ICD-10-CM-based hierarchical outcome tree using incident outcomes identified from hospital and outpatient diagnoses. We used an adjusted P≤0.01 as the threshold for statistical alert to prioritize associations for evaluation as repurposing signals. We varied the analyses by tree size, scanning level, and clinical settings for outcomes. There were 80,510 matched SGLT2i-DPP4i initiator pairs with 215,333 outcomes among SGLT2i initiators and 223,428 outcomes among DPP4i initiators. There were 18 prioritized associations, which included chronic kidney disease (P=0.0001), an expected signal, and anemia (P=0.0001). Heart failure (P=0.0167), another expected signal, was identified slightly beyond the statistical alert threshold. Narrowing the outcome tree, scanning at different tree levels, and including outcomes from different clinical settings influenced the scan statistics. We identified signals aligning with recently approved indications of SGLT2i, plus potential repurposing signals supported by existing evidence but requiring future validation.

Validation of algorithms in studies based on routinely collected health data: general principles.

Clinicians, researchers, regulators, and other decision-makers increasingly rely on evidence from real-world data (RWD), including data routinely accumulating in health and administrative databases. RWD studies often rely on algorithms to operationalize variable definitions. An algorithm is a combination of codes or concepts used to identify persons with a specific health condition or characteristic. Establishing the validity of algorithms is a prerequisite for generating valid study findings that can ultimately inform evidence-based health care. This paper aims to systematize terminology, methods, and practical considerations relevant to the conduct of validation studies of RWD-based algorithms. We discuss measures of algorithm accuracy; gold/reference standard; study size; prioritizing accuracy measures; algorithm portability; and implication for interpretation. Information bias is common in epidemiologic studies, underscoring the importance of transparency in decisions regarding choice and prioritizing measures of algorithm validity. The validity of an algorithm should be judged in the context of a data source, and one size does not fit all. Prioritizing validity measures within a given data source depends on the role of a given variable in the analysis (eligibility criterion, exposure, outcome or covariate). Validation work should be part of routine maintenance of RWD sources.

Glofitamab as a salvage treatment for B-cell lymphomas in the real world: A multicenter study in Taiwan.

BACKGROUND: Glofitamab is a bispecific antibody with promise for treating relapsed/refractory B-cell lymphoma according to a phase 1/2 clinical trial. This study examined its real-world effectiveness. METHODS: This was an investigator-initiated, multicenter retrospective study including 34 patients who had relapsed/refractory B-cell lymphomas after at least three prior lines of therapy and received glofitamab monotherapy in a compassionate use program in Taiwan between January 2021 and October 2022. RESULTS: At a median follow-up of 15.9 months, 56% of patients responded to glofitamab and 23% achieved complete remission. Response to the previous line of therapy significantly correlated with response to glofitamab (p = .020). Most responses were durable; only five out of the 19 responders had documented disease recurrence at the data cutoff date. The estimated progression-free survival (PFS) was 3.2 months, and the estimated 1-year PFS was 33% for the entire cohort. PFS was better for responders than nonresponders (median PFS, 16.9 vs. 1.8 months; 1-year PFS, 60% vs. 0%). Forty-three cytokine release syndrome (CRS) events were observed, three of which were grade 3; all were manageable without glofitamab discontinuation. No immune effector cell-associated neurotoxicity was reported. Among seven hepatitis B virus (HBV) carriers (six had antiviral prophylaxis) and 14 patients with remote HBV (four had antiviral prophylaxis), no HBV reactivation was observed. CONCLUSIONS: In this real-world cohort, glofitamab exhibited effectiveness comparable to trial results without excessive CRS or new safety issues. With appropriate prophylaxis, glofitamab-treated patients with chronic or remote HBV infection are unlikely to experience virus reactivation.

Avatrombopag for the treatment of patients with chemotherapy-induced thrombocytopenia: A case series.

Management of chemotherapy-induced thrombocytopenia (CIT) is challenging, often resulting in chemotherapy treatment delays, dose reduction, and treatment interruption. Randomized trials support the potential efficacy and safety of thrombopoietin receptor agonists in CIT management. A phase III trial of avatrombopag (AVA) demonstrated increased platelet counts (PC) in patients with solid tumours experiencing CIT. To complement those findings, this case series of six patients with solid tumours and CIT is presented. Results from these cases support the clinical benefit of AVA in improving PC and reducing the impact of CIT on tumour treatment, allowing continued therapy without dose reduction or treatment interruption.

Is early-onset colorectal cancer an evolving pandemic? Real-world data from a tertiary cancer center.

BACKGROUND: Early onset Colorectal Cancer (EOCRC), defined as those diagnosed under the age of 50, has been increasing rapidly since 1970. UK data on EOCRC are currently limited and better understanding of the condition is needed. MATERIALS AND METHODS: A single-center retrospective study of patients with EOCRC treated over 9 years (2013-2021) at a large UK cancer center was performed. Clinicopathological features, risk factors, molecular drivers, treatment, and survival were analyzed. RESULTS: In total, 203 patients were included. A significant increase in cases was reported from 2018-2019 (n = 33) to 2020-2021 (n = 118). Sporadic EOCRC accounted for 70% of cases and left-sided tumors represented 70.9% (n = 144). Median duration of symptoms was 3 months, while 52.7% of the patients had de-novo metastatic disease. Progression-free survival after first-line chemotherapy was 6 months (95% CI, 4.85-7.15) and median overall survival (OS) was 38 months (95% CI, 32.86-43.14). In the advanced setting, left-sided primary tumors were associated with a median OS benefit of 14 months over right-sided primaries (28 vs 14 months, P = .009). Finally, primary tumor resection was associated with median OS benefit of 21 months compared with in situ tumors (38 vs 17 months, P < .001). CONCLUSIONS: The incidence of EOCRC is increasing, and survival outcomes remain modest. Raising public awareness and lowering the age for colorectal cancer screening are directions that could improve EOCRC clinical outcomes. There is also a need for large prospective studies to improve the understanding of the nature of EOCRC and the best therapeutic approaches.

Clinical Value of Timely Targeted Therapy for Patients With Advanced Non-Small Cell Lung Cancer With Actionable Driver Oncogenes.

BACKGROUND: A recent real-world study observed that 24% of patients with advanced non-small cell lung cancer (aNSCLC) with actionable driver oncogenes (ADOs) initiated nontargeted therapies before biomarker test results became available. This study assessed the clinical impact of the timing of first-line (1L) targeted therapies (TTs) in aNSCLC. MATERIALS AND METHODS: This retrospective analysis of a nationwide electronic health record-derived deidentified database included patients aged ≥18 years diagnosed with aNSCLC with ADOs (ALK, BRAF, EGFR, RET, MET, ROS-1, and NTRK) from January 1, 2015, to October 18, 2022, by biomarker testing within 90 days after advanced diagnosis and received 1L treatment. Cohorts were defined by treatment patterns ≤42 days after test results: "Upfront TT" received 1L TT ≤42 days; "Switchers" initiated 1L non-TT before or after testing but switched to TT ≤42 days; and "Non-switchers" initiated non-TT before or after testing and did not switch at any time. Adjusted multivariate Cox regression evaluated real-world progression-free survival, real-world time to next treatment or death, and real-world overall survival. RESULTS: A total of 3540 patients met the study criteria; 78% were treated in a community setting, and 50% underwent next-generation sequencing (NGS). There was no significant difference in outcomes between Switchers and Upfront TT; inferior outcomes were observed in Non-switchers versus Upfront TT. CONCLUSION: Our findings demonstrated improved outcomes with upfront 1L TT versus non-TT in patients with aNSCLC with ADOs and observed timely switching to TT after biomarker test result had similar outcomes to Upfront TT. Opportunities remain to improve the use of NGS for early ADO identification and determination of 1L TT.

Tumor Response Predicts Survival Time of Nivolumab Monotherapy for Advanced Gastric Cancer: A Subgroup Analysis of the DELIVER Trial (JACCRO GC-08).

BACKGROUND: This prospective observational study evaluated the real-world effectiveness of nivolumab monotherapy in previously treated advanced gastric cancer (GC). A preplanned 2-year final analysis was performed to confirm survival and tumor behavior with nivolumab monotherapy. PATIENTS AND METHODS: The primary endpoint was overall survival (OS). The data regarding tumor size were prospectively collected and evaluated using the RECIST criteria. Exploratory analyses were performed for survival according to the tumor response and depth of response (DpR) in patients with measurable lesions who were receiving nivolumab monotherapy as third- or later-line therapy. RESULTS: In 487 patients, the median OS and progression-free survival (PFS) were 5.8 (95% CI 5.3-6.9) months and 1.8 (95% CI 1.7-2.0) months, respectively. The response rate (RR) was 14.5% in 282 patients with measurable lesions. In 234 patients treated with third- or later-line, the DpR was found to be associated with PFS and OS in the Spearman analysis (r = 0.55 and 0.44, respectively) as well as using a discrete variable. When the DpR was divided into 5 groups (-20%≥DpR; -20%