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  • Improving Outcomes in Diffuse B-Cell Lymphoma Requires Multidisciplinary Evolution

    Improving Outcomes in Diffuse B-Cell Lymphoma Requires Multidisciplinary Evolution

    Diffuse large B-cell lymphoma (DLBCL) is an aggressive and common form of cancer that impacts thousands of individuals globally. In recent years, the treatment landscape of DLBCL has shifted rapidly due to evolutions in molecular profiling, immunotherapy, and response-adapted monitoring. At the 67th American Society of Hematology Annual Meeting and Exposition, which takes place December 6 through 9 in Orlando, Florida, experts discussed how emerging modalities and novel research insights are powering the next frontier of DLBCL care.1

    Presenters at the session, titled “Now Is the Time to Improve Outcomes in Diffuse Large B-Cell Lymphoma,” included Sarah Rutherford, MD, an associate professor of clinical medicine in the division of hematology/oncology at Weill Cornell Medicine; Jennifer Crombie, MD, a senior physician at Dana Farber Cancer Institute; and Franck Morschhauser, PhD, Centre Hospitalier Universitaire de Lille, Lille, France. Together, the presenters outlined a series of innovations that are helping to inform personalized treatment strategies, in addition to expected challenges as these methods are utilized.1

    Early Response Assessment Could Lead to Treatment Modification, Improved Outcomes in DLBCL

    Improving outcomes in patients with DLBCL begins with earlier response assessments that can be analyzed to determine therapy modifications, according to Jennifer Crombie. Her presentation detailed opportunities for improving prognosis and early detection, including using interim positron emission tomography (iPET) scans and measuring circulating tumor DNA (ctDNA) to detect minimal residual disease (MRD). Crombie explains why utilizing ctDNA could be particularly effective at identifying patients who may benefit from a treatment alteration.1

    After frontline chemotherapy, often consisting of treatment with rituximab (Rituxan; Roche), cyclophosphamide (Cytoxan; Bristol Myers Squibb), doxorubicin (Adriamycin; Pfizer), vincristine (vincristine sulfane injection; Pfizer), and prednisone (R-CHOP) or polatuzumab (Polivy; Genentech) with the R-CHOP regimen, many patients will achieve significant improvements in their disease. For patients who do not exhibit a complete response following cycles of therapy, a PET scan—at the end of treatment—or an iPET scan—in the middle of treatment—determines the state of the cancer and impact of treatment.1

    Crombie described numerous challenges regarding the use of PET scans that could hamper efforts to assess the patient’s cancer. These include imperfections in end-of-treatment PET that, despite predicting progression-free survival (PFS) and overall survival (OS) after first-line (1L) treatment, could miss patients who relapse.1

    “There is a high false-positive rate,” Crombie explained. “It makes you worry about potentially changing the therapy of someone who may be driving benefit [from their current regimen.”1

    Moreover, investigators of response-adapted trials have attempted to derive a clinical benefit with intensive chemotherapy using iPET with little results. In a 10-year follow-up of the PETAL trial (NCT00554164), for example, although iPET predicted outcomes in aggressive lymphoma, iPET-based treatment alterations did not improve outcomes.2-4

    Crombie highlights molecular testing using ctDNA assessments as a more productive avenue, asking the crowd, “Can we do better?” She outlined a series of next-generation sequencing assays for MRD, including clonoSEQ (Adaptive Biotechnologies Corporation), CAPP-Seq (Roche), and PhasED-Seq (Foresight Diagnostics). Recent studies demonstrate improved personalized cancer profiling and heightened sensitivity with these novel diagnostic assays, especially in Roschewski et al, who demonstrated that PhasED-Seq can be prognostic at both interim and end-of-therapy assessments.1,5,6

    Barriers remain erected against the use of interim MRD in clinical practice, including workflow and turnaround time considerations, along with a lack of commercial availability of diagnostic assays. However, Crombie envisions a future where frontline induction—whether it be chemotherapy or a novel agent—could be followed by iPET and interim ctDNA assessment, with results that can guide future treatment plans. These interim assessments could play a complementary role in future DLBCL treatment.1

    “We’re not there yet, but this is, I think, an attractive potential strategy to consider for the future,” Crombie explained. “And I hope clinical trials start to answer these types of questions, as to whether or not we can use MRD and PET scans in this fashion.”1

    Optimizing Treatment Sequencing in Second and Third Lines

    Novel modalities of response assessments in the form of ctDNA MRD could transform how DLBCL is treated. But how do health care professionals determine exactly which treatments to utilize in each patient in relapsed or refractory disease, especially given the myriad novel therapies and regimens now available? Franck Morschhauser explained how this consideration finds itself at the forefront of a shifting field, which is transitioning from defining patients after the 1L based on their transplant eligibility to defining them on their eligibility for chimeric antigen receptor (CAR) T-cell therapy.1

    CAR T-cell therapies have transformed the paradigm of second-line treatment in DLBCL. In phase 2 trials such as ALYCANTE (NCT04531046) and PILOT (NCT03483103), agents like axicabtagene ciloleucel (axi-cel, Yescarta; Gilead Sciences) and lisacabtagene maraleucel (liso-cel, Breyanzi; Bristol Myers Squibb) have demonstrated strong PFS rates within 1 year. CAR T-cell therapy carries numerous advantages compared with autologous stem cell transplantation, including not requiring a response from a prior line of therapy and not necessitating a referral to a specialty setting. Still, Morschhauser cautions providers that “eligibility for CAR T-cell therapy is a dynamic process,” noting that older adults and patients with comorbidities face a higher risk of neurotoxicities.1,7-10

    While new CAR T-cell therapies are becoming standard of care options, bispecific antibodies (BsAbs) and combination agents with antibody-drug conjugates are pushing treatment capabilities even further. Investigators have tested regimens such as glofitamab (Columvi; Genentech) plus gemcitabine and oxaliplatin, mosunetuzumab (Lunsumio; Genentech) plus polatuzumab vedotin, and polatuzumab vedotin, rituximab, gemcitabine, and oxaliplatin. The sheer number of combinations provides countless new ways to better treat patients with DLBCL in the relapsed or refractory setting, Morschhauser explained.1,11-13

    Still, Morschhauser noted that data on the impacts of prior BsAb exposure on CAR T-cell outcomes remains limited; he told the audience that “we should be very cautious…before making a decision to shift the sequence in the other direction.” Given the unanswered questions that remain in the field, Morschhauser gave his preference in the second line setting towards CAR T-cell therapy. However, in the third line—following the failure of CAR T-cell therapy—Morschhauser discussed the merits of treatment with BsAbs. Research led by Topp et al previously demonstrated the effectiveness of monotherapy with the BsAb odronextamab in patients with disease progression after CAR T-cell therapy.1,14

    “Patients experiencing disease progression after CAR T and bispecifics still have [significant] unmet need, and we should focus our research on those patients,” Morschhauser concluded.1

    REFERENCES
    1. Crombie J, Morschhauser F, Rutherford S. “Now Is the Time to Improve Outcomes in Diffuse Large B-Cell Lymphoma.” Presented: 67th American Society of Hematology (ASH) Annual Meeting and Exposition; December 6, 2025; Orlando, FL; Orange County Convention Center; Tangerine Ballroom. Accessed via ASH Virtual Platform on December 6, 2025.
    2. Kostakoglu L, Martelli M, Sehn LH, et al. End-of-treatment PET/CT predicts PFS and OS in DLBCL after first-line treatment: results from GOYA. Blood Adv. 2021;5(5):1283-1290. doi:10.1182/bloodadvances.2020002690
    3. Dührsen U, Bockisch A, Hertenstein B, et al. Response-guided first-line therapy and treatment of relapse in aggressive lymphoma: 10-year follow-up of the PETAL trial. Blood Neoplasia. 2024;1(3):100018. doi:10.1016/j.bneo.2024.100018
    4. Positron emission tomography guided therapy of aggressive non-Hodgkin’s lymphomas (PETAL). ClinicalTrials.gov Identifier: NCT00554164. Last Updated May 5, 2017. Accessed December 6, 2025. https://www.clinicaltrials.gov/study/NCT00554164
    5. Falchi L, Jardin F, Haioun C, et al. Glofitamab (Glofit) plus R-CHOP has a favorable safety profile and induces high response rates in patients with previously untreated (1L) large B-cell lymphoma (LBCL) defined as high risk by circulating tumor DNA (ctDNA) dynamics: Preliminary safety and efficacy results. Presented: 65th A American Society of Hematology (ASH) Annual Meeting and Exposition; December 11, 2023; San Diego, CA. Accessed Online December 6, 2025. https://ash.confex.com/ash/2023/webprogram/Paper173953.html
    6. Roschewski M, Kurtz DM, Westin JR, et al. Remission assessment by circulating tumor DNA in large B-cell lymphoma. J Clin Oncol. 2025;43(34):3652-3661. doi:10.1200/JCO-25-01534
    7. Houot R, Bachy E, Cartron G, et al. Axicabtagene ciloleucel as second-line therapy in large B cell lymphoma ineligible for autologous stem cell transplantation: a phase 2 trial. Nature Medicine. 2023;29:2593-2601. doi:10.1038/s41591-023-02572-5
    8. Axi-cel as a 2nd line therapy in patients with relapsed/refractory aggressive B lymphoma ineligible to autologous stem cell transplantation. ClinicalTrials.gov Identifier: NCT04531046. Last Updated October 9, 2024. Accessed December 6, 2025. https://clinicaltrials.gov/study/NCT04531046
    9. Sehgal A, Hoda D, Riedell PA, et al. Lisocabtagene maraleucel as second-line therapy in adults with relapsed or refractory large B-cell lymphoma who were not intended for haematopoietic stem cell transplantation (PILOT): an open-label, phase 2 study. Lancet Oncol. 2022;23(8):1066-1077. doi:10.1016/S1470-2045(22)00339-4
    10. Lisocabtagene maraleucel (JCAR017) as second-line therapy (TRANSCEND-PILOT-017006). ClinicalTrials.gov Identifier: NCT03483103. Last Updated December 12, 2023. Accessed December 6, 2025. https://clinicaltrials.gov/study/NCT03483103
    11. Abramson JS, Ku M, Hertzberg M, et al. Glofitamab plus gemcitabine and oxaliplatin (GemOx) versus rituximab-GemOx for relapsed or refractory diffuse large B-cell lymphoma (STARGLO): a global phase 3, randomised, open-label trial. Lancet. 2024;404(10466):1940-1954. doi:10.1016/S0140-6736(24)01774-4
    12. Westin J, Zhang H, Kim W, et al. Mosunetuzumab plus polatuzumab vedotin is superior to R-GemOx in transplant-ineligible patients with R/R LBCL: primary results of the Phase III SUNMO trial. Presented: 2025 International Conference on Malignant Lymphoma Annual Meeting; June 17 to 21, 2025; Lugano, Switzerland. Accessed Online December 6, 2025. https://medically.gene.com/global/en/unrestricted/haematology/ICML-2025/icml-2025-presentation-westin-mosunetuzumab-plus-polatu.html
    13. Matasar M, Li Z, Vassilakopoulos TP, et al. Polatuzumab vedotin, rituximab, gemcitabine and oxaliplatin (Pola-R-GemOX) for relapsed/refractory (r/r) diffuse large b-cell lymphoma (DLBCL): results from the randomized phase III POLARGO trial. Presented: European Hematology Association Congress 2025; June 12 to 15, 2025; Milan, Italy. Accessed Online December 6, 2025. https://library.ehaweb.org/eha/2025/eha2025-congress/4159178/matthew.matasar.polatuzumab.vedotin.rituximab.gemcitabine.and.oxaliplatin.html
    14. Topp MS, Matasar M, Allan JN, et al. Odronextamab monotherapy in R/R DLBCL after progression with CAR T-cell therapy: primary analysis of the ELM-1 study. Blood. 2025;145(14):1498-1509. doi:10.1182/blood.2024027044

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  • Can The Rest Is Football Netflix deal succeed?

    Can The Rest Is Football Netflix deal succeed?

    Juventus FC/Getty Images Gary Lineker sits in a football stand smiling, with another stand across the pitch seen behind him out of focus.Juventus FC/Getty Images

    While he was presenting Match of the Day and other football coverage for the BBC, Lineker was building his podcast business in the background

    “He’s officially the top dog, isn’t he,” former Man City defender Micah Richards…

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  • Dhurandhar Full Movie Collection: ‘Dhurandhar’ box office collection Day 2: Ranveer Singh’s spy actioner shows good growth on Saturday; crosses Rs 50 crore mark |

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    Ranveer Singh’s high-octane spy thriller ‘Dhurandhar’, directed by Aditya Dhar, is off to a powerful start at the box office, showing good growth and impressive momentum as it powers through its debut weekend.Dhurandhar Movie ReviewAfter…

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  • Capital cities lead, while other cities lag in the EU

    Economic growth in the EU has been persistently slower than in the US over the past two decades. Economic growth has been slowing, mainly due to weakening labour productivity growth according to the Draghi Report (Draghi 2024). While much of the debate has focused on investment gaps, regulatory barriers, and labour market dynamics at the national level, less attention has been paid to the role of economic structure at a fine geographical scale in shaping Europe’s diverging growth trajectories.

    Our recent analysis (Dijkstra et al. 2025) aims to fill this gap by building on previous studies (Enflo 2010, Le Gallo and Kamarianakis 2011, Gómez-Tello et al. 2020, Kilroy and Gana 2020, Martin et al. 2018) and using novel data from the Annual Regional Database of the European Commission (ARDECO). Armed with these data, we examine for the first time productivity dynamics across metropolitan regions (‘metros’) in Europe over the period 2001–2021 with a ten-sector disaggregation analysis.

    The results reveal a nuanced geography of economic growth. In capitals, growth was fuelled by both productivity growth and employment growth, which may explain why they also saw the highest population growth (Table 1). In other metropolitan areas, however, employment, productivity, and populations grew at half the rate of capitals. In the rest of the EU (i.e. non-metros), populations shrank and employment barely grew, but labour productivity grew almost as fast as in capitals.

    Table 1 Decomposing the growth of gross value added (GVA) per capita in EU capitals, other metros, and non-metro regions, 2001-2021

    Note: A decomposition means that growth is split into its components:  GVA per capita growth = Productivity growth + Employment over population growth (A = B + C); Employment per capita growth = Employment growth – Population growth (C = D – E).

    When we look at the drivers of productivity growth, one pattern stands out: productivity growth occurred mostly within economic sectors rather than through shifts to more productive sectors in all three types of regions, although its relative importance varied. Capitals experienced high productivity growth, but employment growth was higher in less productive sectors, suggesting that the concentration of highly productive sectors – such as finance and professional services – generates more demand for employment in other sectors, such as retail, arts, and sports (Moretti 2012). Other metros and non-metros also achieved part of their growth through higher employment growth in more productive sectors, reflecting the fact that structural transformations are still ongoing.

    Changes in employment by sector confirm this. Between 2001 and 2021, capital regions expanded their employment shares in services (e.g. information and communication services, professional services), while employment in industry, and trade, transport, and hotels declined (Figure 1). Other metropolitan regions followed a similar but less pronounced trajectory. In contrast, non-metropolitan regions remained more dependent on traditional sectors and experienced limited employment growth. This implies that the shift of employment happened through reductions in employment in industry and agriculture rather than through labour expansion.

    Figure 1 Employment per sector by type of region in the EU in 2001, 2011, and 2021

    Productivity growth over the period 2001-2021 was fuelled by:

    • capital city status (capital metro regions lead growth, concentrating both economic and political power; see Figure 2);
    • population density (but not enough to prevent other metro regions from lagging behind);
    • lower initial productivity levels, showing signs of convergence;
    • patenting activity, as well as the employment share in ICT and finance; and
    • good transport infrastructure.

    Figure 2 Labour productivity growth in capitals and other metros, 2001-2021

    Our findings suggest that productivity at the local level is more nuanced than simply “cities are good and other places are lagging”. The findings contribute to the growing debate on agglomeration economies and labour productivity inequalities. Specifically, our work underscores the need to assess why other metro regions have underperformed over the past two decades, and whether non-metro regions will continue to converge or whether their growth will stall once they have transitioned to more productive sectors.

    Innovation can increase regional productivity, as shown in our regression analysis and the literature. This analysis is relevant for regional development policy, especially in the context of the debate on EU cohesion policy in the next programming period.  Our study highlights the different trends in productivity growth and sectoral composition of capitals, other metros and non-metros. This suggests that a tailored approach to address the distinct challenges and opportunities of different regional contexts may be more successful. Furthermore, the findings can help to identify strategies that enhance European competitiveness by embracing regional specificities (Capello and Rodríguez-Pose 2025).

    References

    Capello, R and A Rodríguez-Pose (2025), “Europe’s quest for global economic relevance: On the productivity paradox and the Draghi report”, Scienze Regionali 24(1): 7-15.

    Dijkstra, L, M Kompil and P Proietti (2025), “Are cities the real engines of growth in the EU?”, Geography and Environment Discussion Paper No. 2025, LSE.

    Draghi, M (2024), The future of European competitiveness, European Commission.

    Enflo, K S (2010), “Productivity and employment—Is there a trade-off? Comparing Western European regions and American states 1950–2000”, The Annals of Regional Science 45(2): 401-421.

    Gómez‐Tello, A, M J Murgui‐García and M T Sanchis‐Llopis (2020), “Exploring the recent upsurge in productivity disparities among European regions”, Growth and Change 51(4): 1491-1516.

    Kilroy, A and R Ganau (2020), “Economic growth in European Union NUTS-3 regions”, Finance, Competitiveness and Innovation Global Practice, World Bank.

    Le Gallo, J and Y Kamarianakis (2011), “The evolution of regional productivity disparities in the European Union from 1975 to 2002: A combination of shift–share and spatial econometrics”, Regional Studies 45(1): 123-139.

    Martin, R, P Sunley, B Gardiner, E Evenhuis and P Tyler (2018), “The city dimension of the productivity growth puzzle: the relative role of structural change and within-sector slowdown”, Journal of Economic Geography 18(3): 539-570.

    Moretti, E (2012), The New Geography of Jobs, Houghton Mifflin Harcourt.

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  • Apple quietly removes Night Mode Portraits on iPhone 17 Pro, leaving users puzzled

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  • ‘The Boys’ Season 5 Trailer, Release Date Unveiled

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  • TV tonight: a mega new Doctor Who spin-off from Russell T Davies | Television & radio

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  • This AI Model Can Intuit How the Physical World Works

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    The original version of this story appeared in Quanta Magazine.

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