Temporal trends in relative survival of diffuse large B‐cell lymphoma in Sweden and Denmark in the era of targeted and cellular therapies

Diffuse large B-cell lymphoma (DLBCL) is a B-cell neoplasm characterized by an aggressive clinical course.1 Approximately one-fourth of the patients starting primary treatment with curative intent are treatment refractory or relapse during the initial follow-up and subsequently have a much worse prognosis.2, 3 New targeted and cellular therapies have shown unprecedented response rates and duration of responses in relapsed/refractory DLBCL.4-6 In Sweden, CAR (chimaeric antigen receptor) T-cell therapy was approved in 2019, but in Denmark, a neighbouring country with a similar health-care structure, CAR T was not approved until 2023. Bispecific antibodies (i.e. glofitamab, epcoritamab) have been available from 2017 to 2018 and onwards in clinical trials in both countries, but are not yet approved for routine use.7, 8 In this study, we aimed to assess temporal trends in survival among DLBCL patients in Sweden and Denmark overall with special focus on the most recent calendar period when CAR T was approved in Sweden but not in Denmark. We identified all DLBCL patients ≥18 years (ICD-O/3: 96783 96803 96883 97123 97373 97383 97353) in the Swedish Lymphoma Register (SLR) (n = 9343) and the Danish Lymphoma Register (LYFO) (n = 6709) diagnosed 2007–2021. Patients with transformed indolent lymphomas were excluded. SLR and LYFO are national quality-of-care registers that contain detailed information regarding lymphoma characteristics, treatment and survival.9, 10 During the study period, Swedish and Danish National treatment guidelines both recommended R-CHOP as primary treatment for most DLBCL patients, suggesting the addition of etoposide or other intensive treatment protocols adding high-dose cytarabine (HD-AraC) and methotrexate (HD-Mtx) for younger high-risk patients. The recommendations for relapsed/refractory patients were also similar, suggesting second-line regimens R-DHAP/DHAX, R-ICE or R-GDP and consolidation with high-dose treatment (BEAM) with autologous stem-cell transplantation (ASCT). In 2014–2017, the first Swedish DLBCL patients (n = 15) were treated with CAR T in an academic trial.11 Since December 2019, CAR T (axi-cel) has been a treatment option in clinical routine for DLBCL following ≥2 prior lines of therapy in Sweden, and 49 patients were treated with axi-cel through 2022 (1 in 2019, 7 in 2020, 17 in 2021 and 24 in 2022) (median age 63 (17–76) years). Two-thirds of these patients were diagnosed in 2019 or later (n = 33, 67%). In this study, patients were followed from diagnosis to death or administrative censoring (31 December 2022), whichever came first. Survival was assessed in 3-year calendar periods (2007–2009, 2010–2012, 2013–2015, 2016–2018, 2019–2021). We estimated temporal trends in overall survival (OS), using the Kaplan–Meier estimator, and in relative survival (RS), using the Pohar-Perme estimator.12 For RS, information about expected mortality in comparable groups from the general population (by country, sex, age and calendar year) was retrieved from the Human Mortality Database (mortality.org). OS and RS were stratified by sex, age at diagnosis (≤40, 41–50, 51–60, 61–70, 71–80, >80 years) and age-adjusted International Prognostic Index (aaIPI). Patients with aaIPI < 2 were classified as low risk and aaIPI ≥ 2 as high risk. To compare differences in OS and RS, we used the log-rank test (for OS) and the log-rank type test proposed by Grafféo (for RS).13 Flexible parametric survival models were used to estimate adjusted excess mortality rate ratios (EMRR) (see Table S1 for model details). For statistical analyses, we used R14 and Stata.15 For RS estimates and tests, we used the relsurv16 and rstmp2 packages. The Swedish cohort included 8833 DLBCL patients and the Danish cohort included 6291 patients. Median age at DLBCL diagnosis increased from 70 (2007–2009) to 74 years (2019–2021) in Sweden, and from 67 to 72 years in Denmark over the same period. The distribution of risk group (high vs. low based on aaIPI) was stable across calendar time when stratified by age (≤70/>70 years) at diagnosis (Table 1; Table S2). In the Swedish cohort, the 2-year OS was 66% (95% CI: 64–68) for patients diagnosed in the earliest calendar period (2007–2009) which increased to 71% (95% CI: 69–73) in the most recent period (2019–2021) (p < 0.001) (Figure 1; Tables S3 and S4). Consistent improvements in RS were also observed; the 2-year RS improved from 70% (95% CI: 67–72) to 75% (95% CI: 73–78) (p < 0.001). In the Danish cohort, the 2-year OS was 67% (95% CI: 64–70) for patients diagnosed in the earliest calendar period (2007–2009) and 70% (95% CI: 68–73) in the most recent period (2019–2021) (Figure 1; Tables S3 and S4). Two-year RS improved from 70% (95% CI: 67–73) to 74% (95% CI: 71–77) during the same period. Among young high-risk patients in Sweden (≤70, aaIPI ≥ 2), 2-year RS improved from 70% (95% CI: 66–75) in the earliest calendar period to 82% (95% CI: 77–87) in the most recent period (p < 0.001) (Figure 2). The largest improvement was noted in the most recent period compared to the period before (2016–2018, 2-year RS 75%, 95% CI: 71–80). For Danish young high-risk patients (≤70, aaIPI ≥ 2), 2-year RS improved from 67% (95% CI: 62–73) in the earliest calendar period to 77% (95% CI: 72–82) in the most recent period (p = 0.005). However, there was no improvement in the most recent period compared to the period before (2016–2018, 2-year RS 78%, 95% CI: 73–83) (Figure 2). For older patients, we observed a more moderate increase across risk groups (Figures S1 and S2). Adjusted analyses confirmed lower excess mortality over calendar time among all patients from 2007–2009 to 2019–2021 in both the Swedish (EMRR 0.71, 95% CI: 0.62–0.82; Table S5) and the Danish cohort (EMRR 0.74, 95% CI: 0.63–0.87; Table S6). For young high-risk patients in Sweden (≤70, aaIPI ≥ 2), the excess mortality was 30% lower (EMRR 0.70, 95% CI: 0.50–0.97) when comparing the most recent calendar period (2019–2021) to the one before (2016–2018) adjusting for age and sex. In the Danish cohort, there was no equivalent difference in excess mortality during the two most recent periods among young high-risk patients (EMRR 2019–2021 1.03 (95% CI: 0.74–1.45) compared to 2016–2018). In this bi-national population-based study, we observed a continuous improvement in survival for DLBCL patients over the last 15 years across all ages and risk groups, in spite of a parallel increase in age at diagnosis to well above 70 years. In Sweden, young high-risk patients (≤70 and aaIPI ≥ 2) demonstrated a particular improvement in survival from 2019 and onwards, with a 2-year RS of 82% (compared to 75% in 2016–2018). This improvement may at least in part be attributable to the introduction of CAR T as standard third or later line treatment of relapsed/refractory DLBCL patients in late 2019, as no other new treatments were introduced in clinical routine in the relapsed/refractory setting among young patients at the same time. However, it is uncertain whether the observed improvement is mainly a direct effect of CAR T, as treated patients remain relatively few. We cannot exclude additional indirect effects on patient survival just from the paradigmatic change in availability of more potent therapy in the relapsed/refractory setting, resulting in a higher treatment ambition. Interestingly, we did not observe the same improvement in RS among young high-risk patients in Denmark, where CAR T was not yet approved until 2023. In the interpretation of the observed survival trends, we also need to consider the potential impact of modifications in primary treatment schemes. The Nordic trials CRY-04 and CHIC (conducted in 2004–2008 and 2011–2014, respectively) included young DLBCL patients (<65 years) with aaIPI 2–3 who were treated with R-CHOP with the addition of etoposide, HD-Mtx and/or HD-AraC and reported over 80% OS in this high-risk population.17, 18 Observational studies have also suggested the addition of etoposide to be beneficial for younger patients.19, 20 However, since intensified treatment protocols did not prove to be superior to R-CHOP in randomized trials, it is uncertain if these intensified schemes have had a decisive impact on a national level.21 Polatuzumab–vedotin in combination with rituximab–bendamustine was approved in Sweden in 2020 and may also have contributed to prolonged survival among older patients with relapsed/refractory disease. Furthermore, general improvements in supportive care over time, such as widespread use of prophylactic medications to reduce infectious complications and increased availability of home care, could have contributed across all age groups. Strengths of this study include the population-based design using national register data in two countries with similar healthcare systems and virtually no loss to follow up. This allowed us to study demographic changes over time in the entire DLBCL population. A limitation is that we lack detailed treatment information at the individual level for relapsed/refractory patients, and hence, we could not disentangle specific reasons for the observed improved survival over time. In summary, in this large register study, we observed a continuous improvement for DLBCL patients from the rituximab era into the era of targeted and cellular therapies in two Nordic countries, in parallel with an increasing age at diagnosis. Encouragingly, a significant improvement in survival in the most recent calendar period in young high-risk patients, coinciding with the introduction of CAR T in routine care, was only observed in Sweden. Further studies are warranted to better understand the underlying causes of the observed survival improvements in different patient groups. SH: Writing original draft (lead), writing—review and editing (lead); SE: Data curation (supporting); formal analysis (supporting); writing original draft (lead); writing—review and editing (equal). SA: Data curation (lead, Swedish data); formal analysis (lead, Swedish data) writing—review and editing (equal). MRS: Data curation (lead, Danish data); formal analysis (lead, Danish data); writing—review and editing (equal). TCE-G: Conceptualization (supporting), writing—review and editing (equal). KES: Conceptualization (lead), funding acquisition (lead), writing—review and editing (equal). KS, PB, BEW, P-OA, JJ, MJ, CBP and GE all contributed to the writing—review and editing process (equal). The study was supported by the Swedish Cancer Society and by grants provided by the Regional Agreement on Medical Training and Clinical Research (ALF) between the Stockholm County Council and Karolinska Institutet to KES. TCEG received funding from the Danish Cancer Society. MRS was supported by the Danish Data Science Academy, which is funded by the Novo Nordisk Foundation (NNF21SA0069429) and VILLUM FONDEN (40516). P-O Andersson has research funding from Gilead and honoraria from Abbvie, AstraZeneca, Beigene, Lilly, Janssen, SOBI and Takeda. P Brown was on advisory boards for Abbvie, Gilead, Novartis, Roche and Swedish Orphan. G Enblad has received honoraria from Merck and Pierre Fabre. Advisory board: Roche and Gilead. Scientific advisor: Elicera Therapeutics AB. M Jerkeman has research funding from AstraZeneca, Roche, Abbvie and honoraria from Abbvie, Janssen and Kite/Gilead. JM Jørgensen has received honoraria from Abbvie, Roche, Kite/Gilead, Novartis, SOBI, Caribou and Incyte. KE Smedby has received research funding from Janssen Pharmaceuticals NV and honoraria from Abbvie and Incyte. BE Wahlin has research funding from Incyte. For the remaining authors, no relevant conflicts of interest were declared. The data underlying this study are available at the Swedish and Danish National Board of Health and Welfare and Statistics Sweden and Denmark, respectively, for investigators with the appropriate ethical approvals, but restrictions apply. However, data can be made available from the authors upon reasonable request for meta-analyses, and with the appropriate approvals from the Swedish and/or the Danish Ethical Review Authority (https://etikprovningsmyndigheten.se and https://researchethics.dk). Figure S1. Figure S2. Table S1. Table S2. Table S3. Table S4. Table S5. Table S6. 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