Tarec Christoffer El-Galaly1, Diego Villa2, Thomas Yssing Michaelsen3, Martin Hutchings4, Nabegh George Mikhaeel5, Kerry J Savage2, Laurie H Sehn2, Sally Barrington6, Jakob W Hansen4, Daniel Smith5, Kirsty Rady7, Karen J Mylam8, Thomas S Larsen8, Staffan Holmberg9, Maja B Juul10, Sabrina Cordua11, Michael R Clausen12, Kristina B Jensen13, Hans E Johnsen14, John F Seymour7, Joseph M Connors2, Peter de Nully Brown4, Martin Bøgsted14, Chan Y Cheah15. 1. Department of Hematology, Aalborg University Hospital, Mølleparkvej 4, DK-9100 Aalborg, Denmark; Clinical Cancer Research Center, Aalborg University Hospital, Sdr. Skovvej 15, 9100 Aalborg, Denmark; Department of Clinical Medicine, Aalborg University, Sdr. Skovvej 15, DK-9000 Aalborg, Denmark. Electronic address: tarec.galaly@gmail.com. 2. Division of Medical Oncology, British Columbia Cancer Agency Centre for Lymphoid Cancer and the University of British Columbia, 150-686 W. Broadway, Vancouver, BC, Canada. 3. Department of Hematology, Aalborg University Hospital, Mølleparkvej 4, DK-9100 Aalborg, Denmark. 4. Department of Hematology, Rigshospitalet, Copenhagen University Hospital, Blegdamsvej 9 DK-2100 Copenhagen, Denmark. 5. Department of Clinical Oncology, Guy's and St Thomas' Hospital, Westminster Bridge Road, London SE1 7EH, UK. 6. PET Imaging Centre, Division of Imaging Sciences and Biomedical Engineering, King's College London, King's Health Partners, St. Thomas' Hospital, Westminster Bridge Road, London SE1 7EH, UK. 7. Department of Haematology, Peter MacCallum Cancer Centre and University of Melbourne, 305 Grattan Street, Melbourne VIC 3000, Australia. 8. Department of Hematology, Odense University Hospital, Søndre Boulevard 29, DK-5000 Odense, Denmark. 9. Department of Hematology, Herlev Hospital, Copenhagen University Hospital, Herlev Ringvej 75, DK-2730 Herlev, Denmark. 10. Department of Hematology, Vejle Hospital, Kabbeltoft 25, DK-7100 Vejle, Denmark. 11. Department of Hematology, Roskilde Hospital, Zealand University Hospital, Sygehusvej 10, DK-4000 Roskilde, Denmark. 12. Department of Hematology, Aarhus University Hospital, Tage-Hansens Gade 2, DK-8000 Aarhus, Denmark. 13. Department of Hematology, Holstebro Hospital, Lægårdvej, DK-7500 Holstebro, Denmark. 14. Department of Hematology, Aalborg University Hospital, Mølleparkvej 4, DK-9100 Aalborg, Denmark; Clinical Cancer Research Center, Aalborg University Hospital, Sdr. Skovvej 15, 9100 Aalborg, Denmark; Department of Clinical Medicine, Aalborg University, Sdr. Skovvej 15, DK-9000 Aalborg, Denmark. 15. Department of Haematology, Peter MacCallum Cancer Centre and University of Melbourne, 305 Grattan Street, Melbourne VIC 3000, Australia; Department of Hematology, Sir Charles Gairdner Hospital and Pathwest Laboratory Medicine, Hospital Ave, Nedlands WA 6009, Australia; University of Western Australia, 35 Stirling Hwy, Crawley, WA 6009, Australia.
Abstract
PURPOSE: Development of secondary central nervous system involvement (SCNS) in patients with diffuse large B-cell lymphoma is associated with poor outcomes. The CNS International Prognostic Index (CNS-IPI) has been proposed for identifying patients at greatest risk, but the optimal model is unknown. METHODS: We retrospectively analysed patients with diffuse large B-cell lymphoma diagnosed between 2001 and 2013, staged with PET/CT and treated with R-CHOP(-like) regimens. Baseline clinicopathologic characteristics, treatments, and outcome data were collected from clinical databases and medical files. We evaluated the association between candidate prognostic factors and modelled different risk models for predicting SCNS. RESULTS: Of 1532 patients, 62 (4%) subsequently developed SCNS. By multivariate analysis, disease stage III/IV, elevated serum LDH, kidney/adrenal and uterine/testicular involvement were independently associated with SCNS. There was a strong correlation between absolute number of extranodal sites and risk of SCNS; the 144 patients (9%) with >2 extranodal sites had a 3-year cumulative incidence of SCNS of 15.2% (95% confidence interval [CI] 9.2-21.2%) compared with 2.6% (95% CI 1.7-3.5) among those with ≤2 sites (P < 0.001). The 3-year cumulative risks of SCNS for CNS-IPI defined risk groups were 11.2%, 3.1% and 0.4% for high-, intermediate- and low-risk patients, respectively. All risk models analysed had high negative predictive values, but only modest positive predictive values. CONCLUSIONS: Patients with >2 extranodal sites or high-risk disease according to the CNS-IPI should be considered for baseline CNS staging. Clinical risk prediction models suffer from limited positive predictive ability, highlighting the need for more sensitive biomarkers to identify patients at highest risk of this devastating complication.
PURPOSE: Development of secondary central nervous system involvement (SCNS) in patients with diffuse large B-cell lymphoma is associated with poor outcomes. The CNS International Prognostic Index (CNS-IPI) has been proposed for identifying patients at greatest risk, but the optimal model is unknown. METHODS: We retrospectively analysed patients with diffuse large B-cell lymphoma diagnosed between 2001 and 2013, staged with PET/CT and treated with R-CHOP(-like) regimens. Baseline clinicopathologic characteristics, treatments, and outcome data were collected from clinical databases and medical files. We evaluated the association between candidate prognostic factors and modelled different risk models for predicting SCNS. RESULTS: Of 1532 patients, 62 (4%) subsequently developed SCNS. By multivariate analysis, disease stage III/IV, elevated serum LDH, kidney/adrenal and uterine/testicular involvement were independently associated with SCNS. There was a strong correlation between absolute number of extranodal sites and risk of SCNS; the 144 patients (9%) with >2 extranodal sites had a 3-year cumulative incidence of SCNS of 15.2% (95% confidence interval [CI] 9.2-21.2%) compared with 2.6% (95% CI 1.7-3.5) among those with ≤2 sites (P < 0.001). The 3-year cumulative risks of SCNS for CNS-IPI defined risk groups were 11.2%, 3.1% and 0.4% for high-, intermediate- and low-risk patients, respectively. All risk models analysed had high negative predictive values, but only modest positive predictive values. CONCLUSIONS:Patients with >2 extranodal sites or high-risk disease according to the CNS-IPI should be considered for baseline CNS staging. Clinical risk prediction models suffer from limited positive predictive ability, highlighting the need for more sensitive biomarkers to identify patients at highest risk of this devastating complication.
Authors: Matthew R Wilson; Toby A Eyre; Nicolas Martinez-Calle; Matthew Ahearne; Katrina E Parsons; Gavin Preston; Jahanzaib Khwaja; Jeremy Schofield; Johnathon Elliot; Almurtadha Mula Kh; Nimish Shah; Cheuk-Kie Cheung; Matthew A Timmins; Thomas Creasey; Kim Linton; Jeffery Smith; Christopher P Fox; Fiona Miall; Kate Cwynarski; Pamela McKay Journal: Blood Adv Date: 2020-08-11
Authors: Magdalena Klanova; Laurie H Sehn; Isabelle Bence-Bruckler; Federica Cavallo; Jie Jin; Maurizio Martelli; Douglas Stewart; Umberto Vitolo; Francesco Zaja; Qingyuan Zhang; Federico Mattiello; Gila Sellam; Elizabeth A Punnoose; Edith Szafer-Glusman; Christopher R Bolen; Mikkel Z Oestergaard; Guenter R Fingerle-Rowson; Tina Nielsen; Marek Trneny Journal: Blood Date: 2019-01-07 Impact factor: 22.113
Authors: Tarec Christoffer El-Galaly; Chan Yoon Cheah; Mette Dahl Bendtsen; Grzegorz S Nowakowski; Roopesh Kansara; Kerry J Savage; Joseph M Connors; Laurie H Sehn; Neta Goldschmidt; Adir Shaulov; Umar Farooq; Brian K Link; Andrés J M Ferreri; Teresa Calimeri; Caterina Cecchetti; Eldad J Dann; Carrie A Thompson; Tsofia Inbar; Matthew J Maurer; Inger Lise Gade; Maja Bech Juul; Jakob W Hansen; Staffan Holmberg; Thomas S Larsen; Sabrina Cordua; N George Mikhaeel; Martin Hutchings; John F Seymour; Michael Roost Clausen; Daniel Smith; Stephen Opat; Michael Gilbertson; Gita Thanarajasingam; Diego Villa Journal: Eur J Cancer Date: 2018-02-21 Impact factor: 9.162