Background Survival rates for hematological malignancies have substantially improved over recent decades, prompting attention to treatment-related side effects and long-term health complications, including cardiovascular disease (CVD). These complications may limit cancer treatment tolerability and contribute to increased morbidity and mortality. Objectives We evaluated the short- and long-term incidence of CVD across hematological malignancies. Methods Adult patients (aged ≥18 years) registered in the Netherlands Cancer Registry from 1995 to 2023 diagnosed with 1 of the 12 most common hematological malignancies were matched with general population control subjects. Data were linked to national hospitalization and cause of death registries to ascertain 11 cardiovascular outcomes. Poisson regression and Fine and Gray competing risks models were used to evaluate absolute and relative CVD risk. Results Among 174,984 patients with hematological malignancies matched with 855,085 control subjects, heart failure incidence was elevated across all malignancy subtypes, with highest excess rates per 1,000 person-years in myelodysplastic syndrome (37.75; 95% CI: 35.60-39.90) and multiple myeloma (24.68; 95% CI: 23.46-25.90). Venous thromboembolism risk peaked within the first year after diagnosis and remained elevated up to 5 years across all malignancies. First-year HRs for deep venous thrombosis ranged from 3.52 (95% CI: 2.58-4.80) in chronic lymphocytic leukemia to 34.04 (95% CI: 19.83-58.44) in Hodgkin lymphoma. Conclusions Patients and survivors of hematological malignancies face substantially elevated short- and long-term risk of CVD compared with the general population, varying markedly by malignancy subtype. Identifying patient-, disease-, and treatment-specific drivers of this risk is essential to develop targeted prevention and management strategies to improve outcomes.

Background In patients with hematologic malignancies, COVID-19 vaccine effectiveness is unknown and determinants of severe COVID-19 lack granularity.Methods To identify determinants of SARS-CoV-2 infection outcome we conducted a population-based, nationwide cohort study, including all adult Dutch residents who tested positive for SARS-CoV-2 between 1 June 2020, and 31 March 2022. Individuals were classified as having a (history of) hematologic malignancy, solid malignancy, or no malignancies. Primary outcome was severe COVID-19, defined as COVID-19-related hospitalization or death following first SARS-CoV-2 infection.Results Among 4 649 341 included individuals, those with hematologic malignancies were at highest risk of severe COVID-19. Vaccine effectiveness against severe COVID-19 in patients with hematologic malignancies was up to 74% (95% CI, 60% to 83%), depending on the SARS-CoV-2 variant period, the number of received vaccinations, and the time interval since vaccination. Risk of severe COVID-19 was highest for patients with recently diagnosed hematologic malignancies and declined over time, except for patients with chronic hematologic malignancies. Risk of severe COVID-19 tended to be higher in patients on tumor-specific treatment such as CD38 and CD20 antibodies, proteasome inhibitors, and protein kinase inhibitors.Conclusions COVID-19 vaccination lowered the risk of severe COVID-19 in SARS-CoV-2-infected patients with hematologic malignancies, although these patients remained at elevated risk compared with others. Determinants of severe COVID-19 included type of malignancy, time interval between malignancy diagnosis and SARS-CoV-2 infection, and treatment. These data can guide healthcare professionals in designing additional prevention and therapeutic strategies against respiratory virus infections for patients with hematologic malignancies.

ABSTRACT Comprehensive insights are lacking into why patients with hematological malignancies (HMs) receive no cancer‐directed treatment. We evaluated socio‐demographic and cancer‐related characteristics, decision‐making rationales, and overall survival in patients with three common HMs―diffuse large B‐cell lymphoma (DLBCL), symptomatic multiple myeloma (MM), and acute myeloid leukemia (AML)―who do not receive cancer‐directed treatment, using the nationwide Netherlands Cancer Registry. A total of 26 945 patients diagnosed with DLBCL (47%), symptomatic MM (29%), or AML (25%) between 2014 and 2021 were included. About 16% of the patients did not receive cancer‐directed treatment, ranging from 26% in AML to 15% in DLBCL and 10% in MM. The primary reason for not receiving cancer‐directed treatment in all three HMs was related to physical condition. The second main reason was patient/family choice in DLBCL and MM, whereas in AML it was rapid disease progression. In female patients, patient/family choice was a more prevalent reason for not receiving cancer‐directed treatment than in male patients. Patients with a lower socio‐economic position more often did not receive cancer‐directed treatment. Median OS varied by reason for not receiving cancer‐directed treatment, with the shortest OS in patients experiencing rapid disease progression or death before treatment initiation (0·4 to 0·6 months).

Timely surveillance of cancer treatment requires real-time integration of electronic health records (EHR) data into population-based registries. We validated data from the Datagateway, an automated system that harmonizes structured EHR data across hospitals into a common model to support near real-time enrichment of the Netherlands Cancer Registry (NCR). Data from patients with acute myeloid leukemia, multiple myeloma, lung cancer, and breast cancer were extracted via the Datagateway and compared to NCR data and EHR source data. The system achieved 100% accuracy compared to registered NCR diagnoses, and an accuracy of 95% when comparing new diagnoses to the NCR inclusion criteria. Treatment was correctly identified in all cases, with only 3% of combination therapies misclassified. Laboratory values matched virtually completely; toxicity indicators showed 72%-100% accuracy. Automated real-time EHR data integration using a harmonized model is feasible and reliable, enabling scalable, high-quality support for real-world oncology research.

BACKGROUND:Risk-based analyses are increasingly popular for understanding heterogeneous treatment effects (HTEs) in clinical trials. For time-to-event analyses, the assumption that high-risk patients benefit most on the clinically important absolute scale when hazard ratios (HRs) are constant across risk strata might not hold. Absolute treatment effects can be measured as either the risk difference (RD) at a given time point or the difference in the restricted mean survival time (ΔRMST), which aligns more closely with utilitarian medical decision-making frameworks. We examined risk-based HTE analyses strata in time-to-event analyses to identify the patterns of absolute HTE across risk strata and whether the ΔRMST may lead to better treatment decisions than the RD. METHODS:Using artificial and empirical time-to-event data, we compared the RD-the difference between Kaplan-Meier estimates at a certain time point-and the ΔRMST-the area between the Kaplan-Meier curves-across risk strata and show how these metrics can prioritize different subgroups for treatment. We explored scenarios involving constant HRs while varying both the overall event rates and the discrimination of the risk models. RESULTS:When event rates and discrimination were low, the RD and the ΔRMST increased monotonically, with high-risk patients benefitting more than low-risk patients. As the event rate increased and/or discrimination increased, a 'sweet spot' pattern emerged: intermediate-risk patients benefit more than low-risk and high-risk patients. When the RD was used, the 'sweet spot' pattern emerged, even in circumstances in which the ΔRMST increased across the risk groups, thus understating the benefit for higher-risk patients and potentially leading to treatment mistargeting. CONCLUSION:The pattern of HTE characterized by the RD may diverge substantially from the ΔRMST, potentially leading to treatment mistargeting. Therefore, we recommend the ΔRMST for assessing the absolute HTE in time-to-event data.

Real-world data (RWD) previously contributed to post-marketing regulatory decision-making, but are currently also considered as external controls to single-arm trials. The use of RWD control data may be compromised by methodological issues, urging validation of RWD control cohorts. Two external control cohorts of newly diagnosed acute myeloid leukaemia patients, one registered by the HARMONY Alliance (HA) and one by the Netherlands Cancer Registry (NCR), were compared to the control arm of the randomized HOVON-103 trial (H103 controls). All patients, aged >65 years with a WHO performance score of 0-2 (or missing), received standard induction chemotherapy. 1:1 propensity score calliper matching (PSM) was applied to improve comparability, and overall (OS) and relapse-free survival (RFS) were assessed. Fewer data elements were available in external cohorts compared to H103 controls, specifically in the NCR cohort. Baseline characteristics of the external cohorts differed from H103 controls; missing data were also more frequent and predominantly concerned WHO performance score. After PSM, HA patients demonstrated non-significantly different OS and RFS to H103 controls at 2 years (26 ± 4% vs. 31 ± 5%, p = 0.59; 24 ± 5% vs. 30 ± 6%, p = 0.52), while NCR patients had 12% lower OS (28 ± 4% vs. 40 ± 4%, p = 0.21). Validation of external control cohorts is needed before incorporating RWD control data into comparative analyses, as missing data, specifically comorbidities, and residual confounding may limit comparability.

BACKGROUND:Patients with haematological malignancies are at increased risk of developing skin cancer and often experience worse skin cancer-related outcomes. However, there is a lack of nationwide, population-based data with long-term follow-up on the incidence and risks of different skin cancer types across all haematological malignancies. OBJECTIVES:To assess population-based risk estimates for cutaneous squamous cell carcinoma (cSCC), malignant melanoma (MM), Merkel cell carcinoma (MCC) and basal cell carcinoma (BCC) among patients with haematological malignancies, stratified by skin cancer type and haematological malignancy subgroup. These estimates can serve as a base for surveillance guidelines and patient education. METHODS:This nationwide population-based epidemiological cohort study used data from 210 794 patients diagnosed with a haematological malignancy between 1989 and 2020 from the Netherlands Cancer Registry (NCR). In addition, data on each type of histopathologically confirmed skin cancer per patient after haematological malignancy diagnosis were retrieved from the NCR. Patients with a history of skin cancer prior to their haematological malignancy were excluded. Cumulative incidences, standardized incidence ratios (SIRs) and absolute excess risks for each of the four skin cancers were calculated and stratified by haematological malignancy subgroup, age, sex, follow-up and primary treatment. RESULTS:The overall 10-year cumulative incidence of developing a first skin cancer was 2.6% for cSCC, 0.5% for MM, 0.05% for MCC and 4.8% for BCC. Compared with the general population, nearly all haematological malignancy subgroups showed more than a twofold increased risk of cSCC, MM, MCC and BCC. Patients with chronic lymphocytic leukaemia (CLL) showed the highest risks for each of the four skin cancers, with SIRs of 4.4 for cSCC, 2.7 for MM, 9.3 for MCC, and 2.6 for BCC. These elevated risks persisted for > 30 years after haematological malignancy diagnosis. CONCLUSIONS:Patients with all types of haematological malignancies, and especially those with CLL, have a lifetime increased risk of developing different types of skin cancer. These findings highlight the importance of creating awareness among patients and care providers about this increased risk and promoting sun-protective measures and regular skin self-examinations in this high-risk population.

7000 Background: The prognostic utility of circulating tumor DNA measurable residual disease (ctDNA-MRD) detection at end of treatment (EOT) using phased variant (PV) enrichment and detection sequencing (PhasED-Seq) has been demonstrated in patients with diffuse large B-cell lymphoma (DLBCL) receiving first-line (1L) therapy. Prior studies are limited by treatment, patient, and sample heterogeneity. Here, we independently validate the prognostic value of PhasED-Seq in a national, multi-center study of uniformly treated 1L DLBCL patients. Methods: ctDNA-MRD was assessed using Foresight CLARITY in LBCL patients enrolled on HOVON-902 from >50 centers in the Netherlands and Belgium. Patients were treated with curative-intent 1L therapy (R-CHOP or DA-EPOCH-R). We evaluated the prognostic significance of MRD status [positive (+), negative (-)] on progression-free survival (PFS) and overall survival (OS). PVs were identified from pretreatment biopsies or plasma with matched normal DNA. EOT plasma samples were used for ctDNA-MRD detection. Results: A total of 150 of 156 (96%) eligible patients had successful PV identification. Of included patients, 90%, 9%, and 1% had DLBCL, HGBL, and PBMCL, respectively. IPI distribution was 22% low, 29% low-intermediate, 27% high-intermediate, and 22% high risk; median age was 67.5. The 24-month PFS and OS in this cohort were 74% and 86%, respectively, with 31 months of median follow-up. At the EOT, 76% of patients were MRD- and 24% were MRD+. MRD+ status significantly predicted inferior PFS (2 yr PFS 88 vs 28%; HR 9.7, 95% CI 4.2-22.3, p<0.0001) and OS (2 yr OS 97 vs 50%; HR 10.6, 95% CI 4.1-27.7, p<0.0001). Moreover, in patients without complete response, MRD+ was significantly prognostic for PFS, suggesting an ability to adjudicate imaging results (HR for PFS 7.6, 95% CI 3.6-16.3, p < 0.0001). Among patients who were MRD- and achieved CMR at EOT, 2-year PFS and OS were 91% and 99%, respectively. All patients who failed to achieve CMR and remained MRD+ experienced relapse. ctDNA-MRD was prognostic for outcomes in all subgroups considered, including source of baseline sample (tumor versus plasma), best clinical response, IPI, sex, lactate dehydrogenase, stage, or extranodal disease. In multivariate analysis including ctDNA-MRD, IPI, and best overall response, ctDNA-MRD was significantly and independently prognostic for both PFS [HR for ctDNA: 7.1, 95% CI 3.5-14.3, p<0.0001] and OS [HR for ctDNA: 5.1, 95% CI 2.2-11.9, p=0.00018]. Conclusions: We validated the prognostic value of PhasED-Seq-based ctDNA-MRD in a real-world multicenter 1L DLBCL cohort. This highlights the utility of ctDNA-MRD to confirm residual disease in patients without complete response by imaging, as well as the potential to identify patients who may benefit from consolidation therapy. These results support the integration of MRD as a standard component of response evaluation in 1L DLBCL treatment.

Background:Risk-based analyses are increasingly popular for understanding heterogeneous treatment effects (HTE) in clinical trials. For time-to-event analyses, the assumption that high-risk patients benefit most on the clinically important absolute scale when hazard ratios (HRs) are constant across risk strata might not hold. Absolute treatment effects can be measured as either the risk difference (RD) at a given time point or the difference in restricted mean survival time (ΔRMST) which aligns more closely with utilitarian medical decision-making frameworks. We examined risk-based HTE analyses strata in time-to-event analyses to identify the patterns of absolute HTE across risk strata, and whether ΔRMST may lead to more meaningful treatment decisions than RD. Methods:Using artificial and empirical time-to-event data, we compared RD-the difference between Kaplan-Meier estimates at a certain time point-and ΔRMST-the area between the Kaplan-Meier curves-across risk strata and show how these metrics can prioritize different subgroups for treatment. We explored scenarios involving constant HRs while varying both the overall event rates and the discrimination of the risk models. Results:When event rates and discrimination were low, RD and ΔRMST increased monotonically, with high-risk patients benefitting more than low-risk patients. As the event rate increased and/or discrimination increased: 1) a "sweet spot" pattern emerged: intermediate-risk patients benefit more than low-risk and high-risk patients; and 2) RD understates the benefit in high-risk patients. Conclusions:The pattern of HTE characterized by RD may diverge substantially from ΔRMST, potentially leading to treatment mistargeting. Therefore, we recommend ΔRMST for assessing absolute HTE in time-to-event data. Key messages:To quantify absolute heterogeneous treatment effect (HTE) in time-to-event data, the difference in restricted mean survival time (ΔRMST) is more intuitive and comprehensive, less dependent on the time horizon, and better captures HTE when the hazard ratio (HR) of treatment varies over time, compared to the risk difference (RD).We examined risk-based HTE analyses in time-to-event analyses to identify the patterns of absolute HTE across different risk strata, and whether ΔRMST may lead to more meaningful treatment decisions than RD.Even with a constant HR, intermediate-risk patients may benefit more than low-risk and high-risk patients as event rates increase, a phenomenon known as a "sweet spot" pattern.The RD does not accurately reflect the benefit for high-risk patients when event rates and/or discrimination of the risk model are high, unlike to the ΔRMST.We recommend the ΔRMST for assessing absolute HTE, as the RD may potentially lead to treatment mistargeting.

Chronic lymphocytic leukemia (CLL) manifests heterogeneously with varying outcomes. This population-based study examined causes of death (CODs), as registered by the physician who established the death, among 20,588 CLL patients diagnosed in the Netherlands between 1996 and 2020. Utilizing cause-specific flexible parametric survival models, we estimated cause-specific hazard ratios (HRs) and cumulative incidences of death due to CLL, solid malignancies, other hematological malignancies, infections, and other causes. Our findings reveal CLL as the predominant COD, contributing to around 40% of relative mortality, with a declining 5-year death probability from 16.8% in 1996-2002 to 7.6% in 2010-2020. Also, deaths attributed to solid malignancies, other hematological malignancies, and other COD diminished over time, as evidenced by respective HRs (95% confidence interval) of 0.68 (0.60%-0.77%), 0.45 (0.38%-0.53%), and 0.77 (0.66%-0.90%). In summary, our comprehensive, population-based analysis underscores a noticeable reduction in CLL-attributed deaths and other competing causes over the studied period. Nonetheless, CLL is registered as the most prevalent cause of mortality among contemporary diagnosed patients with CLL, emphasizing the continued relevance of CLL-centric clinical strategies and research.

First-line treatment for advanced-stage diffuse large B-cell lymphoma (DLBCL) typically involves 6x R-CHOP21 or 6x R-CHOP21 with two additional rituximab administrations (6x R-CHOP21 + 2 R). In contemporary practice, this treatment choice might be guided by interim PET scan results. This nationwide, population-based study investigates the comparative effectiveness of these treatment regimens in an era where interim PET-guided treatment decisions were not standard practice. Utilizing the Netherlands Cancer Registry, we identified 1577 adult patients diagnosed with advanced-stage DLBCL between 2014-2018 who completed either 6x R-CHOP21 (43%) or 6x R-CHOP21 + 2 R (57%). We used propensity scores to assess differences in event-free survival (EFS) and overall survival (OS). At five years, EFS (hazard ratio of 6x R-CHOP21 + 2 R versus 6x R-CHOP21 [HR] = 0.89; 95% confidence interval [CI], 0.72-1.09) and OS (HR = 0.93; 95% CI, 0.73-1.18) were not significantly different between both regimens. In exploratory risk-stratified analysis according to the International Prognostic Index (IPI), high-IPI patients (i.e., scores of 4-5) benefit most from 6x R-CHOP21 + 2 R (5-year absolute risk difference of EFS = 16.8%; 95% CI, -0.4%-34.1% and OS = 12.1%; 95% CI, -5.4-29.6%). Collectively, this analysis reveals no significant differences on average in EFS and OS between the two treatments. However, the potential benefits for high-risk patients treated with 6x R-CHOP21 + 2 R underscore the need for future research.

Objective Acute myeloid leukaemia (AML) prognosis is enhanced with intensive remission induction chemotherapy (ICT) in eligible patients. However, ICT eligibility perceptions may differ among healthcare professionals. This nationwide, population-based study aimed to explore regional variation in ICT application and its relation with overall survival (OS).Methods and analysis We compared nine Dutch regional networks using data from the Netherlands Cancer Registry. Regional variance was assessed for the entire population and age subgroups (ie, ≤60 years and >60 years) using multivariable mixed effects logistic and Cox proportional hazard regression analyses, expressed via median OR (MOR) and median HR (MHR).Results Including all adult AML patients from 2014 to 2018 (N=4060 patients; 58% males; median age, 70 years), 1761 (43%) received ICT. ICT application varied from 36% to 57% (MOR 1.36 (95% CI 1.11 to 1.58)) across regions, with minor variations for patients aged ≤60 years (MOR 1.16 (95% CI 1.00 to 1.40)) and more extensive differences for those aged >60 years (MOR 1.43 (95% CI 1.16 to 1.63)). Median OS spanned 4.9–8.4 months across regions (MHR 1.11 (95% CI 1.00 to 1.15)), with pronounced differences in older patients (MHR 1.12 (95% CI 1.08 to 1.20)) but negligible differences in the younger group (MHR 1.02 (95% CI 1.00 to 1.14)). Survival differences for the total population and the older patients decreased to respectively, MHR 1.09 (95% CI 1.00 to 1.13) and 1.10 (95% CI 1.04 to 1.18), after additional adjustment for the probability of receiving ICT within a region, indicating approximately 10% unexplained differences.Conclusion Regional disparities in ICT application and survival exist, especially in older AML patients. However, ICT application differences partially explain survival disparities, indicating the need for more standardised ICT eligibility criteria and a better understanding of underlying causes of outcome disparities.

Importance:The use of real-world data (RWD) external control arms in prospective studies is increasing. The advantages, including the immediate availability of a control population, must be balanced with the requirements of meeting evidentiary standards. Objective:To address the question of whether and to what extent the methods of RWD studies compare to standard methods used in randomized clinical trials. Evidence Review:A systematic search across 4 electronic databases and Google Scholar was conducted from January 1, 2000, to October 23, 2023. Studies were included in the systematic review if they compared an intervention arm in a clinical trial to an RWD control arm in patients with hematological cancers and if they were published between 2000 and 2023. Findings:Thirty-two prospective intervention studies incorporating external control data from RWD sources of patients with hematological cancers were identified. A total of 4306 patients from intervention arms and 10 594 from RWD control arms were included across all studies. Only 2 studies (6%) included prospectively collected RWD. The complete trial inclusion criteria were applied to the RWD cohort in 7 studies (22%). Four studies (13%) published the statistical analysis plan and prespecified use of RWD. A total of 23 studies (72%) applied matching algorithms for trial and RWD cohorts, including matching for demographic, disease, and/or therapy-related characteristics. The end point criteria were the same as the trial in 8 studies (25%). In contrast, 12 studies (38%) used different end points, and 12 (38%) did not provide an end point definition for the RWD. Twelve studies (38%) had a median follow-up difference of less than a year between arms. Eight studies (25%) reported toxic effect data for the trial arm, of which 5 studies reported toxic effect data for the RWD arm. Conclusions and Relevance:In this systematic review, limitations were observed in the application of clinical trial eligibility criteria to RWD, statistical rigor and application of matching methods, the definition of end points, follow-up, and reporting of adverse events, which may challenge the conclusions reported in studies using RWD.

Background: Acute myeloid leukemia (AML) requires specialized care, particularly when administrating intensive remission induction chemotherapy (ICT). High-volume hospitals are presumed more adept at delivering this complex treatment, resulting in better overall survival (OS) rates. Despite its potential implications for quality improvement, research on the volume-outcome relationship in ICT administration for AML is scarce. This nationwide, populationbased study in the Netherlands explored the volume-outcome relationship in AML. Materials and methods: Data from the Netherlands Cancer Registry on adult (>= 18 years of age) ICT-treated AML patients, diagnosed between 2014 and 2018, were analyzed. Hospital volume was assessed against OS using mixedeffects Cox regression, adjusting for patient and disease characteristics (i.e. case mix), with hospital as a random effect. Results: Our study population consisted of a total of 1761 patients (57% male), with a median age of 61 years. The average annual number of ICT-treated patients varied across the 24 hospitals (range 1-56, median 13, and interquartile range 8-20 patients per hospital per year). Overall, an increase of 10 ICT-treated patients annually was associated with an 8% lower mortality risk [hazard ratio (HR) 0.92, 95% confidence interval (CI) 0.87-0.98, P = 0.01]. This association was not significant at 30-day (HR 1.02, 95% CI 0.89-1.17, P = 0.75) and 42-day (HR 0.96, 95% CI 0.85-1.08, P = 0.54) OS but became apparent Conclusions: There is a volume-outcome association within AML care. This finding could support hospital volume as a metric in AML care. However, it should be acknowledged that centralizing care is a complex process with implications for health care providers and patients. Therefore, any move toward centralization must be judiciously balanced.

Background Patients with relapsed or refractory (R/R) diffuse large B-cell lymphoma (DLBCL) have a dismal prognosis. Encouragingly, the treatment landscape of R/R DLBCL is rapidly evolving with treatments such as CAR T-cell therapy and bispecific antibodies that significantly improve the prognosis for particular patient subsets. The SCHOLAR-1 study, the first to provide a benchmark for future clinical trials in R/R DLBCL, described outcomes in R/R DLBCL patients based on data from 2 large randomized trials and 2 academic databases. Since SCHOLAR-1 is not population-based, any extrapolation of the study results to a daily practice population requires caution. Currently, population-based studies confirming findings from SCHOLAR-1 are lacking. Therefore, our nationwide, population-based study aimed to validate the results of SCHOLAR-1 in patients with DLBCL in contemporary clinical practice. Methods We selected all adult DLBCL patients, including transformed follicular lymphoma (tFL) and primary mediastinal B-cell lymphoma (PMBCL), diagnosed between 2014-2016 in the Netherlands from the nationwide Netherlands Cancer Registry (NCR). Data on treatment and survival were available in the NCR with follow-up until December 31, 2021. Inclusion criteria similar to SCHOLAR-1 were used: (i) diagnosis of DLBCL, tFL, or PMBCL, (ii) treatment with an anti-CD20 monoclonal antibody and an anthracycline in first-line, (iii) refractory disease defined as stable disease or progressive disease as the best response to therapy or relapse ≤12 months after autologous stem cell transplantation (ASCT), (iv) and initiation of subsequent treatment at the first instance of refractory disease. Patients were divided into 3 subgroups (i.e., primary refractory, refractory to ≥ second-line treatment, and relapsed ≤12 months post-ASCT) based on the first instance of refractory disease. Descriptive statistics and the Kaplan-Meier method were used to analyze baseline characteristics and overall survival (OS), respectively, after the start of treatment for the first instance of refractory disease. OS was measured until death or the end of follow-up (December 31, 2021). Results Between 2014-2016, 4,085 adult DLBCL patients were diagnosed in the Netherlands, of whom 275 (7%) met the above described criteria (i, ii and iii) for R/R DLBCL. Of these 275 patients, 122 (44%) received subsequent treatment for the first instance of refractory disease. These 122 patients were included in our analytical cohort (61% male, median age: 63 years (IQR: 51-69), 70% Ann Arbor stage III-IV) and mainly comprised DLBCL (87%), followed by tFL (9%) and PMBCL (4%). Forty-six percent had primary refractory disease, 36% was refractory to ≥ second-line treatment and 18% relapsed ≤12 months post-ASCT. The best response to subsequent treatment was assessed for 86 patients, with an overall response rate and complete remission rate of 23% (N=20) and 14% (N=12), respectively. The median OS from the start of subsequent treatment was 3.5 months (95% confidence interval [CI], 2.5-4.3 months), with a 2-year OS rate of 11% (95% CI, 6-17%) (Figure 1A). More specifically, the median OS across the 3 refractory disease subgroups was 3.2 (95% CI, 1.8-4.2 months), 2.5 (95% CI, 1.7-4.3 months), and 9.2 months (95% CI, 3.0-13.9 months), respectively. The corresponding 2-year OS rates were 13% (95% CI, 5-23%), 2% (95% CI, 0.2-10%), and 23% (95% CI, 8-41%), respectively (Figure 1B). Conclusions To contextualize results for R/R DLBCL patients in daily practice, population-based studies are vital to validate results derived from clinical trials or academic databases. Remarkably, more than 50% of the 275 patients meeting refractory disease criteria in our cohort had to be excluded, as they did not receive subsequent treatment at the first instance of refractory disease. Also, compared to SCHOLAR-1, patients with refractory disease in our study had an even lower median OS of 3.5 months (95% CI, 2.5-4.3 months) vs. 6.3 months (95% CI, 5.9-7.0 months) and a lower 2-year OS rate of 11% (95% CI, 6-17%) vs. 20% (95% CI, 16-23%). Our results emphasize the need to improve the dismal prognosis of patients with R/R DLBCL. The real-world data in this study support future research (e.g., benchmarking) and facilitate comparison of (cost-)effectiveness of novel treatments with usual care for patients with DLBCL in clinical practice. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Topic: 19. Aggressive Non-Hodgkin lymphoma - Clinical Background: Outcomes of patients with diffuse large B-cell lymphoma (DLBCL) who are refractory to or who relapse early after first-line therapy (i.e., “early R/R” DLBCL) are generally poor. Second-line treatment options for early R/R DLBCL include salvage immunochemotherapy followed by autologous stem cell transplantation (ASCT) for younger, fit patients and non-intensive regimens for older and unfit patients. In 2022, the European Medicines Agency approved the first CAR T-cell therapy (axicabtagene ciloleucel; axi-cel) to treat adults with early R/R DLBCL based on the results of the pivotal phase 3 ZUMA-7 trial. ZUMA-7 showed the efficacy of axi-cel for early R/R DLBCL patients eligible for second-line therapy with intensive, potentially curative therapy. With the emergence of novel second-line treatment options, evaluating the standard of care (SoC) for early R/R DLBCL in a real-world setting is necessary. However, these data are hitherto scarce. Aims: As a benchmark for novel treatments, we evaluated population-based outcomes of SoC in second-line for early R/R DLBCL patients in the Netherlands in the pre-CAR-T era. Methods: We selected adult patients (≥18 years) with DLBCL, transformed follicular lymphoma (tFL), and primary mediastinal B-cell lymphoma (PMBCL) diagnosed between 2014-2018 from the nationwide Netherlands Cancer Registry. Three inclusion criteria were used and based on ZUMA-7: 1) first-line treatment with an anti-CD20 monoclonal antibody and an anthracycline, 2) early R/R disease defined as either stable/progressive disease as best response to first-line treatment or partial/complete response and subsequent relapse ≤12 months from completion of first-line treatment, and (3) second-line treatment with an intensive regimen ±ASCT. Patients who received CAR T-cell therapy were excluded. Descriptive statistics were used to analyze baseline characteristics at the start of second-line treatment. Survival was assessed from start of second-line treatment until progression, start of subsequent treatment, death, or end of follow-up, whichever occurs first (event-free survival, EFS), or until death or end of follow-up (overall survival, OS), using the Kaplan-Meier method. Results: Of the 6,899 adult patients diagnosed with DLBCL, tFL, and PMBCL in the Netherlands between 2014-2018, 527 received second-line treatment for early R/R disease. After excluding patients who received non-intensive regimens (n=186) and CAR T-cell therapy recipients (n=33), 308 patients were included in our cohort (median age: 60 years; 7% ≥70 years; 66% males; 61% stage III-IV, 90% DLBCL, 6% tFL, 4% PMBCL). In 36% (n=111/308) of the included patients the intensive regimen was followed by ASCT. For 266 patients, the best response to second-line treatment was available, with overall response and complete remission rates of 51% (n=157) and 32% (n=98), respectively. With ≥3 years of follow-up, the median EFS was 3.3 months (95% confidence interval [CI], 2.7-4.2), with a 2-year EFS rate of 27% (95% CI: 22-32; Figure 1A). The median OS was 7.1 months (95% CI: 6.3-8.7), with a 2-year OS rate of 32% (95% CI: 27-38; Figure 1B). Summary/Conclusion: This population-based study demonstrated that in the real world pre-CAR-T era the survival of early R/R DLBCL patients treated with second-line intensive therapy ±ASCT is poor, highlighting the need for novel treatments to improve outcomes. Real-world data on SoC and population estimates facilitate comparison of (cost-)effectiveness and budget impact of novel treatments with usual care in clinical practice and help to shape the future treatment landscape for early R/R DLBCL.Keywords: Diffuse large B cell lymphoma, Real world data, relapsed/refractory, Outcome

Knowledge about evolution of clonal hematopoiesis, which may drive malignant progression, is crucial for clinical decision-making. We investigated the landscape of clonal evolution by error-corrected sequencing on 7,045 sequential samples from 3,359 individuals in the prospective population-based Lifelines cohort, with a special focus on cytosis and cytopenia. Spliceosome (SRSF2/U2AF1/SF3B1) and JAK2 mutated clones show highest growth rates over a median 3.6-year period, while clone sizes for DNMT3A and TP53 increase only marginally, independent of cytosis or cytopenia. Nevertheless, large differences are observed between individuals carrying the same mutation, indicative of modulation by non-mutation-related factors. Clonal expansion is not dependent on classical cancer risk factors (e.g., smoking). Risk for incident myeloid malignancy diagnosis is highest for JAK2, spliceosome, or TP53 mutations and absent for DNMT3A, and it is mostly preceded by cytosis or cytopenia. The results provide important insight into high-risk evolutionary patterns to guide monitoring of “CHIP” and “CCUS.”