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74 citation(s) found for "Mwangi, Raphael".

Prognostic significance of cell-of-origin, gene expression profiles, and frontline therapy in predicting secondary CNS lymphoma in newly diagnosed diffuse large B-cell lymphoma
Falade, Ayo, Mwangi, Raphael, Okcu, Izel, Ravindra, Aditya, Pradeep, Aishwarya, Hampel, Paul, Zanwar, Saurabh, Khan, Muhammad Azeem, Vodicka, Prokop, Klanova, Magdalena, Masar, Michal, Nedved, Adrienne, Khurana, Arushi, Durani, Urshila, Paludo, Jonas, Andrade-Gonzalez, Xavier, Thanarajasingam, Gita, Bennani, N. Nora, Thompson, Carrie, Hricko, Samuel, Janikova, Andrea, Wang, Yucai, Johnston, Patrick, Ivana, Micallef, Novak, Anne, King, Rebecca, Maurer, Matthew, Witzig, Thomas, Ansell, Stephen, Mou, Eric, Habermann, Thomas, Nowakowski, Grzegorz, Bisneto, Jose Villasboas, Trneny, Marek, Cerhan, James, Abeykoon, Jithma, Okcu, Izel , Falade, Ayo, Mwangi, Raphael, Ravindra, Aditya, Pradeep, Aishwarya, Hampel, Paul, Zanwar, Saurabh, Khan, Muhammad Azeem, Vodicka, Prokop, Klanova, Magdalena, Masar, Michal, Nedved, Adrienne, Khurana, Arushi, Durani, Urshila, Paludo, Jonas, Andrade-Gonzalez, Xavier, Thanarajasingam, Gita, Bennani, N. Nora, Thompson, Carrie, Hricko, Samuel, Janikova, Andrea, Wang, Yucai, Johnston, Patrick, Ivana, Micallef, Novak, Anne, King, Rebecca, Maurer, Matthew, Witzig, Thomas, Ansell, Stephen, Mou, Eric, Habermann, Thomas, Nowakowski, Grzegorz, Bisneto, Jose Villasboas, Trneny, Marek, Cerhan, James, Abeykoon, Jithma

Mayo Clinic

Blood | December 4, 2025 | Volume: 146 | Issue: Supplement 1 | Pages: 473-473

10.1182/blood-2025-473 Get It

Abstract Background Secondary central nervous system lymphoma (SCNSL) is a rare but significant complication, affecting approximately 2–10% of patients with diffuse large B-cell lymphoma (DLBCL), often leading to poor outcomes. The CNS-International Prognostic Index (CNS-IPI) remains a widely adopted tool for estimating CNS relapse risk; however, recent advances in molecular profiling and evolving treatment paradigms have challenged the adequacy of CNS-IPI alone in guiding risk assessment. This study evaluates the prognostic relevance of CNS-IPI in conjunction with molecular and clinical factors, specifically cell-of-origin (COO), gene expression, and frontline treatment regimens. The aim is to refine risk stratification and identify patients at highest risk for SCNSL. Method Building on our previous study, we analyzed data from patients with newly diagnosed DLBCL between 2002 and 2023, enrolled in the Mayo Clinic/University of Iowa Lymphoma Molecular Epidemiology Resource. Patients with primary CNS lymphoma, CNS involvement at diagnosis, or who received CNS-directed therapy were excluded. COO was determined using the Hans algorithm and/or Nanostring profiling. Multivariate cause-specific Cox regression models were used to estimate hazard ratios (HR) and 95% confidence intervals (CIs) for predictors of CNS relapse that were measured at the time of initial DLBCL diagnosis. Cumulative incidence with competing risks and cause-specific Cox models were used to analyze relapse risk. Result We included 2137 patients in our analysis, median age at diagnosis was 63 (IQR 53-72), with 41.6% (n=890) females. The albumin level was below normal in 32.5% (n=350), 64.0% (n=1367) had CNS-IPI of intermediate/high, 37.5% (n=586) had non-germinal center B-cell (GCB) COO, and 14.5% (n=309) were double expressor positive. At a median follow-up of 83 months (IQR 42 -143), 82 (3.8%) SCNSL relapses were observed; the 3 and 5 yrs cumulative incidence for SCNSL from time of DLBCL diagnosis were 3.7% (95% CI 3.0-4.7) and 3.8% (95% CI 3.1-4.8) respectively. In models accounting for death as a competing risk, the 5-year cumulative SCNSL incidence estimate for patients with a CNS-IPI low was 1.5% (95% CI 0.8-2.7), Intermediate was 4.9% (95% CI 3.7-6.4), and high was 6.1% (95% CI 3.8-9.6). The 5-year cumulative SCNSL incidence estimate for patients with non-GCB COO was 5.2% (95% CI 3.6-7.4) compared to 2.4% (95% CI 1.6-3.6; p=0.001) for GCB patients, and the 5-year cumulative SCNSL incidence for double expressor positive patients was 8.6% (95% 5.8-12.6) compared to 1.5% (95% CI 0.8-2.7; p<0.001) for double expressor negative patients. In a multivariable model (including CNS-IPI, COO, double expressor, treatment group, extranodal involvement, and albumin group), CNS-IPI intermediate (HR 2.85 [1.58-5.14]; p<0.001) and high (HR 4.31 [2.15-8.65]; p<0.001), non-GCB COO (HR 2.36 [1.37-4.06]; p=0.002], double expressor (HR 5.56 [2.88-10.73]; p<0.001), and below normal albumin (HR 1.89 [1.02-3.50]; p=0.042) were independently associated with increased risk of SCNSL. The majority of the SCNSL relapse occurred within the first 2 years after DLBCL diagnosis; 81.7% (n=67), with only 6.1% (n=5) occurring after 5 years. For patients who developed SCNSL, the median OS from the time of SCNSL diagnosis was 24 months (95% CI 17-34), with 5 years OS of 31% (95% CI 22-43). These findings are being validated using an external, international cohort, and final analysis will be presented at the time of presentation at ASH. Conclusion In this large, prospectively followed cohort with long-term follow-up data, SCNSL remains a rare but devastating complication of DLBCL, with a 5-year cumulative incidence of 3.8% and it is associated with very poor long-term survival. While CNS-IPI remains a strong predictor of SCNSL risk, our study identifies non-GCB COO and double expressor phenotype as independent, additive molecular risk factors. These findings suggest that current risk stratification tools may underestimate the risk of CNS relapse in molecularly defined high-risk subgroups. Considering the poor outcomes linked to SCNSL and the absence of a connection with frontline treatment types, future research should aim to enhance risk prediction models through molecular profiling and explore prophylactic strategies to reduce the likelihood of SCNSL.
Development and validation of a gene expression signature to predict early events in patients with follicular lymphoma
Ramsower, Colleen , Wright, George W. , Cerhan, James R. , Maurer, Matthew J. , Mwangi, Raphael , Novak, Anne J. , Link, Brian K. , Witzig, Thomas E. , Smith, Sonali M. , Friedberg, Jonathan W. , Rimsza, Lisa M. , Witzig, T.E. , Ramsower, Colleen A , Wright, George , Cerhan, James R , Maurer, Matthew , Rosenthal, Allison , Novak, Anne J , Link, Brian K , Kridel, Robert , Shadman, Mazyar , Smith, Sonali M , Friedberg, Jonathan W , Scott, David W , Steidl, Christian , Rimsza, Lisa M , Li, Hongli , Habermann, Thomas M. , LeBlanc, Michael , Shadman, Mazyar , Scott, David W. , Steidl, Christian

Mayo Clinic

Blood Advances | September 18, 2025 | Volume: 9 | Issue: 24 | Pages: 6443-6454

10.1182/bloodadvances.2025016827 | PMID 40966421 Get It

Abstract Although follicular lymphoma (FL) typically follows an indolent course, patients with FL who experience early events, such as transformation or progression, have increased risk of death related to lymphoma. The FL24Cx is an algorithm based on a 45-target gene expression profiling (GEP) assay, which was developed and trained using 265 formalin-fixed, paraffin-embedded tissue samples on a reliable platform to predict, at the time of diagnosis, whether a patient will experience an event within 24 months. The modeling also confirmed and relied upon previously reported synergy between immune response (IR) gene expression signatures IR1 and IR2. Once locked, the 5-factor logistic regression FL24Cx model was independently validated in a retrospectively assessed cohort of 232 patients from 2 immunochemotherapy-treated arms of SWOG Cancer Research Network S0016 phase 3 clinical trial, in which it assigned 169 patients to the low-risk group with 29 events before 24 months (17.2%) and 63 patients to the high-risk group with 24 events before 24 months (38.1%). The relative risk of an event within 24 months after registration among patients who were classified into the high-risk group relative to patients who were classified into the low-risk group was 2.2 (95% confidence interval, 1.41 to 3.51). An up-front GEP biomarker, such as the FL24Cx, rigorously validated in a clinical laboratory and with a clinically relevant turnaround time, could identify and steer enrollment of patients at high risk for early events in clinical trials, thus enabling timely interpretation of such trials and increasing the pace of innovation.
122 | IDENTIFYING HARMFUL HYPERINFLAMMATION IN DIFFUSE LARGE B‐CELL LYMPHOMA USING THE OHI (OPTIMIZED HLH INFLAMMATORY) INDEX—DISCOVERY AND VALIDATION IN REAL‐WORLD PATIENTS
Zoref‐Lorenz, Adi , Cahn, Elliot, Cholack, George , Wang, Y., Gysbers, Brianna J. , Mwangi, Raphael , Nowakowski, Grzegorz S. , Ansell, Steven M., Novak, A. J., Jordan, Michael B. , Cholack, George A , Mou, Eric , Maurer, Matthew J. , Feldman, Andrew L. , Itchaki, Gilad , Habermann, Thomas M. , Link, Brian K. , Witzig, Thomas E. , Cerhan, James R.

Mayo Clinic

Hematological Oncology | June 16, 2025 | Volume: 43 | Issue: S3 | Pages: No page available

10.1002/hon.70093_122 Get It

126 | THE EARLY‐STAGE CLASSIC HODGKIN LYMPHOMA INTERNATIONAL PROGNOSTICATION INDEX (E‐HIPI): AN INDIVIDUALIZED PREDICTION MODEL UTILIZING OBJECTIVE AND CONTINUOUS VARIABLES
Rodday, Angie May, Upshaw, Jenica , Counsell, Nicholas , Cui, Zhongguang, Xiang, Qiaojun , Mwangi, Raphael , Gallamini, Andrea , Hay, Alex E. , Raemaekers, John, Evens, Andrew M. , Rodday, Angie Mae , Maurer, Matthew J. , Rossetti, S., Chang, C., Xiang, Q., Advani, Ranjana H. , André, Marc , Hay, A. E., Hodgson, David , Hoppe, Richard T. , Hutchings, Martin , Johnson, Peter , Mou, Eric , Opat, Stephen , Savage, Kerry J. , Parsons, Susan K. , Radford, John

Mayo Clinic

Hematological Oncology | June 16, 2025 | Volume: 43 | Issue: S3 | Pages: No page available

10.1002/hon.70093_126 Get It

307 | IMPACT OF CELL OF ORIGIN, GENE REARRANGEMENTS, FRONTLINE TREATMENT ON INCIDENCE OF CENTRAL NERVOUS SYSTEM LYMPHOMA RELAPSE IN NEWLY DIAGNOSED LARGE B‐CELL LYMPHOMA
Falade, A. S., Mwangi, Raphael , Hampel, Paul J. , Zanwar, Saurabh , Andrade‐Gonzalez, X., Thanarajasingam, Gita , Novak, Anne J. , Wang, Y., Thompson, Carrie A. , Micallef, Ivana N. , Ansell, Stephen M. , Abeykoon, Jithma P. , Mina, S. A., Paludo, Jonas , Mou, Eric , Durani, Urshila , Maurer, Matthew J. , Link, Brian K. , Cerhan, James R. , Habermann, Thomas M. , Villasboas, José C.

Mayo Clinic

Hematological Oncology | June 16, 2025 | Volume: 43 | Issue: S3 | Pages: No page available

10.1002/hon.70094_307 Get It

224 | REGULAR ASPIRIN USE PRIOR TO DIAGNOSIS AND FOLLICULAR LYMPHOMA PROGNOSIS: NOVEL ASSOCIATION WITH SUPERIOR EVENT‐FREE SURVIVAL
Cholack, George , Mwangi, Raphael , Bisneto, J. V., Robinson, Don, Witzig, T. E., Ansell, Steven M., Novak, Anne J. , Thompson, Carrie A. , Nowakowski, G. S., Wang, Y., Cholack, George A , Bisneto, J. V., Habermann, Thomas M. , Feldman, Andrew L. , Mou, Eric , Slager, Susan L. , Maurer, Matthew J. , Wang, Yucai , Cerhan, James R.

Mayo Clinic

Hematological Oncology | June 16, 2025 | Volume: 43 | Issue: S3 | Pages: No page available

10.1002/hon.70094_224 Get It

Clinical characteristics and treatment outcomes of hepatosplenic T-cell lymphoma: Mayo Clinic experience.
Mina, Syeda A. , Mwangi, Raphael , Hampel, Paul J. , Thanarajasingam, Gita , Thompson, Carrie A. , Nedved, Adrienne, Klebig, Robin, Nowakowski, Grzegorz S. , Ansell, Stephen M. , Bennani, Nabila Nora, Abeykoon, Jithma P., Falade, Ayo , Paludo, Jonas , Hilal, Talal , Durani, Urshila , Moustafa, Muhamad Alhaj , Cerhan, James R. , Habermann, Thomas M. , Witzig, Thomas E. , Abeykoon, Jithma P.

Mayo Clinic

Journal of Clinical Oncology | May 28, 2025 | Volume: 43 | Issue: 16_suppl | Pages: 7075-7075

10.1200/jco.2025.43.16_suppl.7075 Get It

7075 Background: Hepatosplenic T-cell lymphoma (HSTCL) is a rare, aggressive peripheral T-cell lymphoma arising primarily from γδ T-cells. It carries a poor prognosis and resists conventional chemotherapy. Most reports on HSTCL are case-based. This study comprehensively analyzes a large cohort, evaluating treatment strategies and survival outcomes. Methods: This retrospective study included patients (pts) with pathologically confirmed HSTCL diagnosed between 2000-2024, consecutively seen at Mayo Clinic MN. Clinical, pathological, genomic, and treatment-related data were extracted when available. Descriptive statistics were used to summarize baseline characteristics. Time-to-event analyses, including Kaplan-Meier estimates, median overall survival (OS), and survival time estimates were conducted from the date of diagnosis. Results: A total of 20 patients with newly diagnosed HSTCL were included, with a median age of 57 years (range: 35-71). The cohort was predominantly male (70%) and non-Hispanic (93%). Molecular data was available for five patients, revealing abnormalities in STAT5B, MLL3 deletion, TP53, EZH2, TERT, and NF1 E291D . The median follow-up was 27.6 months (m) with a median OS of 17.6 m (95% CI: 11.2 - NA). First-line treatment was anthracycline-based in 68% of pts and non-anthracycline-based in 32%, with higher response rates in the latter group (50% vs.83%). Although non-anthracycline regimens showed a trend toward improved 3-year OS (100% vs. 29%) the difference was not statistically significant (p = 0.16). Achieving a complete response to first-line therapy was also associated with a trend towards a better 3-year OS compared to refractory disease (80% vs. 50%, p = 0.17). Most pts (79%) underwent hematopoietic stem cell transplant (HSCT), primarily allogeneic, with only one receiving autologous HSCT. First-line therapy before HSCT was evenly distributed between anthracycline (55%) and non-anthracycline (45%) regimens. HSCT recipients had significantly higher 3-year OS than non-recipients (83% vs. 33%, p = 0.017). Notably, the patient with a TP53 mutation has remained in remission for over a year post-allogeneic HSCT. Conclusions: HSTCL predominantly affects younger pts, with nearly half dying within a year. Allogeneic HSCT, rarely used in other NHL subtypes, improved survival. Non-anthracycline regimens and achieving CR trended toward better outcomes. Our study, leveraging a sizable cohort, highlights the need for targeted research and novel therapies to improve HSTCL management. Summary of survival outcomes in HSTCL. Characteristics Median OS (y) 3-Year OS (95% CI) 1.48 [0.93- NA] 46% [0.26 - 0.81] Transplant Transplant NA [NA - NA] 83% [0.58 - 1.00] No Transplant 1.02 [0.93 - NA] 33% [0.07 - 1.00] Treatment Anthracycline Based 1.02 [0.36 - NA] 29% [0.11 - 0.73] Non-Anthracycline Based 4.61 [NA- NA] 100% [1.00 - 1.00]
The optimized HLH inflammatory index: A novel prognostic tool for newly diagnosed patients with diffuse large B-cell lymphoma—Discovery and validation.
Lorenz, Adi Zoref, Cahn, Elliot, Feldman, Andew L., Negaard, Brianna J, Mwangi, Raphael , Nowakowski, Grzegorz S. , Ansell, Stephen M. , Novak, Anne J. , Witzig, T. E., Jordan, Michael B. , Mou, Eric , Wang, Yucai , Maurer, Matthew J. , Gysbers, Brianna J. , Itchaki, Gilad , Habermann, Thomas M. , Link, Brian K. , Goyal, Gaurav , Cerhan, James R.

Mayo Clinic

Journal of Clinical Oncology | May 28, 2025 | Volume: 43 | Issue: 16_suppl | Pages: 7073-7073

10.1200/jco.2025.43.16_suppl.7073 Get It

7073 Background: The Optimized HLH Inflammatory (OHI) index (Zoref-Lorenz et al., Blood , 2022), based on serum soluble CD25 (sCD25) and ferritin, is a prognostic tool identifying inflammation in the hemophagocytic lymphohistiocytosis (HLH) spectrum and early mortality risk. Prior studies were retrospective and enriched with HLH-suspected cases. We hypothesized that the OHI index would predict outcomes in unselected diffuse large B-cell lymphoma (DLBCL). Methods: 670 newly diagnosed DLBCL patients from a prospective cohort (2002–2015) were analyzed: 335 for discovery and 335 for validation. Pre-treatment serum sCD25 and ferritin levels were quantified via ELISA, and we evaluated original thresholds (sCD25 ≥ 3,900 U/mL; ferritin ≥ 1,000 ng/mL) and developed DLBCL-optimized thresholds (using receiver operator curves) for predicting 500-day mortality. We also evaluated event-free survival (EFS), EFS at 24 months (EFS24), and overall survival (OS). Results: The median age was 64, and 51% were male. Using original thresholds, 4.2% (n=14) of patients were OHI+, with a 5.6-fold higher risk of 500-day mortality (95% CI 1.6–17; p<0.001). Optimized thresholds identified 23.6% (n=78) as OHI+ with a 9.2-fold higher 500-day mortality risk (95% CI 4.0–24; p<0.001). Optimized OHI+ also had a higher risk of EFS24 failure and inferior EFS and OS (Table). OHI+ patients had higher rates of B symptoms (35% vs. 20%; p=0.027), elevated LDH (76% vs. 34%; p<0.001), worse performance status (ECOG ≥2: 38% vs. 12%; p<0.001), and advanced-stage disease (Stage IV: 57% vs 38%; p<0.001), though IPI scores (3–5) were not significantly different (44% vs 36%; p=0.28). Adjusting for age and IPI, OHI+ independently predicted 500-day mortality (OR=5.0; CI 1.9–13; p=0.001), EFS24 failure (OR=3.2; CI 1.5–6.5; p=0.0018), and inferior long-term EFS (HR=2.2; CI 1.1–4.3; p=0.030) and OS (HR=2.0; CI 1.0–4.0; p=0.040) at a median follow up of 9.8 years in living patients. In validation, optimized OHI predicted 500-day mortality, EFS24 failure, and long-term OS and EFS (Table). Cytokine profiling revealed elevated inflammatory markers in OHI+ patients, including IL1a (p=0.008), CCL2 (p=0.03), CXCL10 (p<0.001), and CXCL9 (p<0.001), reflecting systemic hyperinflammation. Conclusions: The OHI index is a powerful predictor of early and long-term outcomes in DLBCL patients. Optimized thresholds identify a larger OHI+ group, highlighting hyperinflammation’s critical role in poor outcomes. These findings support its use in routine management and clinical trial design for novel therapies. Odds ratios or hazard ratios and p-values for optimized OHI+ and DLBCL prognosis. Outcome Discovery Validation OR for 500-day mortality 9.2; p<0.001 4.0; p=0.002 OR for EFS24 failure 5.2; p <0.001 6.3; p<0.001 HR for OS 2.3; p<0.001 1.8; p=0.006 HR for EFS 2.4; p<0.001 2.5; p<0.001
Impact of cell of origin, gene rearrangements, and frontline treatment on incidence of secondary central nervous system lymphoma in newly diagnosed diffuse large B-cell lymphoma.
Mwangi, Raphael , Hampel, Paul J. , Mina, Syeda A. , Zanwar, Saurabh , Andrade-Gonzalez, Xavier , Thanarajasingam, Gita , Novak, Anne J. , Thompson, Carrie A. , Micallef, Ivana N. , Ansell, Stephen M. , Abeykoon, Jithma P., Falade, Ayo , Paludo, Jonas , Mou, Eric , Wang, Yucai , Maurer, Matthew J. , Link, Brian K. , Cerhan, James R. , Habermann, Thomas M. , Villasboas, José C. , Abeykoon, Jithma P.

Mayo Clinic

Journal of Clinical Oncology | May 28, 2025 | Volume: 43 | Issue: 16_suppl | Pages: 7052-7052

10.1200/jco.2025.43.16_suppl.7052 Get It

7052 Background: Secondary central nervous system lymphoma (SCNSL) is a rare but serious complication that occurs in 2-10% of patients (pts) with diffuse large B-cell lymphoma (DLBCL). The CNS-International Prognostic Index (CNS-IPI) is a validated tool used to assess the risk of CNS relapse. However, with advancements in molecular profiling and treatments, the predictors of SCNSL, including the predictive ability of CNS-IPI combined with other molecular markers and treatment regimens, have become uncertain. This study evaluates new prognostic markers for CNS relapse in DLBCL, focusing on cell-of-origin (COO), gene rearrangements, and treatment types. Methods: DLBCL pts enrolled from 2002-2015 in the Mayo Clinic and University of Iowa Lymphoma Molecular Epidemiology Resource were prospectively followed for incidence of CNS relapse. Pts with primary CNS lymphoma or CNS involvement at diagnosis, and pts treated with high-dose methotrexate containing regimens were excluded. COO classification (GCB vs non-GCB) was determined using Hans algorithm and/or NanoString data. Multivariate Cox regression models estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for predictors of SCNSL. Survival analysis was performed from time of DLBCL diagnosis using Cox proportional hazards model. Results: Among 1278 newly diagnosed DLBCL pts included (median age: 63 years; 43.6% female), SCNSL occurred in 46 (3.6%) pts. Pts with SCNSL were more likely to have intermediate/high CNS-IPI scores (80.4%) than pts without SCNSL (63.9%, p=0.02). The 3 yr SCNSL incidence was 0.016 (0.008-0.0033) in low CNS-IPI vs 0.043 (0.031-0.0060) in high CNS-IPI. Those with SCNSL were significantly more likely at baseline to have non-GCB COO (56.3% vs. 36.5%, p=0.02), and advanced stage (76.1% vs. 59.9%, p=0.03) compared to those without SCNSL. The incidence of SCNSL was not influenced by MYC, BCL2, or BCL6 rearrangements, nor by treatment with R-CHOP, R-EPOCH, or other immunochemotherapy regimens. MVA showed that intermediate CNS-IPI (HR 2.32, 95% CI 1.09-4.92, p=0.029), high CNS-IPI (HR 3.59, 95% CI 1.49-8.62, p=0.004), and non-GCB COO (HR 2.19, 95% CI 1.08-4.42, p=0.0029) were independently associated with increased SCNSL risk. After a median follow-up of 12 years (IQR 9–15), overall survival (OS) was 52.1% for the cohort, with OS significantly worse for SCNSL pts (17.4% vs. 53.4%, p<0.001). Conclusions: This large cohort with extensive follow-up highlights the role of COO as an additional prognostic factor for SCNSL while reinforcing CNS-IPI’s prognostic value. Non-GCB COO pts had a higher risk of SCNSL even when adjusted by CNS-IPI risk. Despite advancements in management, SCNSL pts continue to have poor outcomes. Strategies to reduce the incidence of CNS relapse in high-risk pts require further investigation. MER CNS relapse hazard ratios (95% CI). Characteristics Hazard Ratio 95% CI P-Value CNS-IPI Group 0-1 Low Ref Ref Ref 2-3 Intermediate 2.32 1.09 - 4.92 0.029 4+ High 3.59 1.49 - 8.62 0.004 Cell of Origin* GCB Ref Ref Ref non-GCB 2.19 1.08 - 4.42 0.029 Double Hit* non-DHL Ref Ref Ref DHL 1.08 0.14 - 8.3 0.941 Not Done/Missing 1.38 0.76 - 2.51 0.297 Double Expressor* Negative Ref Ref Ref Positive 2.36 0.71 - 7.85 0.162 Not Done/Missing 1.91 0.89 - 4.08 0.097 IC Group* R-CHOP R-EPOCH Ref 1.63 Ref 0.71 - 3.74 Ref 0.249 Other IC 1.18 0.57 - 2.46 0.660 Any EN Involvement* No Ref Ref Ref Yes 0.98 0.51 - 1.88 0.946 Albumin Group* >=Normal Ref Ref Ref <Normal 1.70 0.75 - 3.85 0.201 Head & Neck Involvement* No Ref Ref Ref Yes 0.35 0.048 - 2.63 0.310 *Adjusted by CNS-IPI risk group.