A prognostic model integrating PET-derived metrics and image texture analyses with clinical risk factors from GOYA

Image texture analysis (radiomics) uses radiographic images to quantify characteristics that may identify tumour heterogeneity and associated patient outcomes. Using fluoro‐deoxy‐glucose positron emission tomography/computed tomography (FDG‐PET/CT)‐derived data, including quantitative metrics, image texture analysis and other clinical risk factors, we aimed to develop a prognostic model that predicts survival in patients with previously untreated diffuse large B‐cell lymphoma (DLBCL) from GOYA (NCT01287741). Image texture features and clinical risk factors were combined into a random forest model and compared with the international prognostic index (IPI) for DLBCL based on progression‐free survival (PFS) and overall survival (OS) predictions. Baseline FDG‐PET scans were available for 1263 patients, 832 patients of these were cell‐of‐origin (COO)‐evaluable. Patients were stratified by IPI or radiomics features plus clinical risk factors into low‐, intermediate‐ and high‐risk groups. The random forest model with COO subgroups identified a clearer high‐risk population (45% 2‐year PFS [95% confidence interval (CI) 40%–52%]; 65% 2‐year OS [95% CI 59%–71%]) than the IPI (58% 2‐year PFS [95% CI 50%–67%]; 69% 2‐year OS [95% CI 62%–77%]). This study confirms that standard clinical risk factors can be combined with PET‐derived image texture features to provide an improved prognostic model predicting survival in untreated DLBCL

Predictive value of PET response combined with baseline metabolic tumor volume in peripheral T-cell lymphoma patients

Peripheral T-cell lymphoma (PTCL) is a heterogeneous group of aggressive non-Hodgkin lymphomas with poor outcomes on current therapy. We investigated whether response assessed with PET/CT combined with baseline total metabolic tumor volume (TMTV) could detect early relapse or refractory disease. Methods: From 7 European centers, 140 patients with nodal PTCL who underwent baseline PET/CT were selected. Forty-three had interim PET (iPET) performed after 2 cycles (iPET2), 95 had iPET performed after 3 or 4 cycles (iPET3/4), and 96 had end-of-treatment PET (eotPET). Baseline TMTV was computed with a 41% SUVmax threshold, and PET response was reported using the Deauville 5-point scale. Results: With a median of 43 mo of follow-up, the 2-y progression-free survival (PFS) and overall survival (OS) were 51% and 67%, respectively. iPET2-positive patients (Deauville score ≥ 4) had a significantly worse outcome than iPET2-negative patients (P 230 cm3 and iPET3/4-negative [59%/84%]; TMTV ≤ 230 cm3 and iPET3/4-positive [42%/50%]; TMTV > 230 cm3 and iPET3/4-positive [0%/18%]). Conclusion: iPET response is predictive of outcome and allows early detection of high-risk PTCL patients. Combining iPET with TMTV improves risk stratification in individual patients

Systemic ALCL Treated in Routine Clinical Practice : Outcomes Following First-Line Chemotherapy from a Multicentre Cohort

INTRODUCTION: Brentuximab vedotin (BV)-CHP is the new standard regimen for first-line treatment of systemic anaplastic large cell lymphoma (sALCL). We undertook a retrospective analysis of consecutive patients diagnosed with sALCL, treated in routine practice, to serve as a benchmark analysis for comparison BV-CHP efficacy in routine practice. METHODS: Patients aged 16 years or older with sALCL treated in seven UK and Australian centres and from 14 additional centres from the UK Haematological Malignancy Research Network database (n = 214). Treatment allocation was clinician choice and included best supportive care (BSC). Main outcomes were time to treatment failure (TTF) and overall survival (OS). Multivariable analysis for predictors of both TTF and OS was also undertaken. RESULTS: The median age 52 years (range 16-93), 18% ECOG ≥ 3 and 40% of cases were ALK positive. CHOP (cyclophosphamide, adriamycin, vincristine, prednisolone) was employed in 152 (71%) of patients and CHOEP (CHOP + etoposide) in 4% of patients. For CHOP-treated patients overall response rate (ORR) was 65% and complete response (CR) 47%. Only 9% of patients underwent autologous stem cell transplant (ASCT). With 57 months median follow-up, 4-year TTF and OS were 41.2% (95% CI 33.1-49.1) and 58.9% (95% CI 50.3-66.5) respectively. Multivariable analysis showed ALK+ status was independently associated with superior TTF (HR 0.36, 95% CI 0.21-0.63) but not OS (0.44, 95% CI 0.18-1.07). DISCUSSION: We present a retrospective analysis with mature follow-up of one of the largest multicentre populations of sALCL available, comparable to similar large retrospective studies. ALK status remains a strong predictor of outcomes. CONCLUSION: These data serve as a robust benchmark for BV-CHP as the new standard of care for sALCL. Similar real-world evidence with BV-CHP will be desirable to confirm the findings of ECHELON-2

A multiple myeloma classification system that associates normal B-cell subset phenotypes with prognosis.

Despite the recent progress in treatment of multiple myeloma (MM), it is still an incurable malignant disease, and we are therefore in need of new risk stratification tools that can help us to understand the disease and optimize therapy. Here we propose a new subtyping of myeloma plasma cells (PCs) from diagnostic samples, assigned by normal B-cell subset associated gene signatures (BAGS). For this purpose, we combined fluorescence-activated cell sorting and gene expression profiles from normal bone marrow (BM) Pre-BI, Pre-BII, immature, naïve, memory, and PC subsets to generate BAGS for assignment of normal BM subtypes in diagnostic samples. The impact of the subtypes was analyzed in 8 available data sets from 1772 patients' myeloma PC samples. The resulting tumor assignments in available clinical data sets exhibited similar BAGS subtype frequencies in 4 cohorts from de novo MM patients across 1296 individual cases. The BAGS subtypes were significantly associated with progression-free and overall survival in a meta-analysis of 916 patients from 3 prospective clinical trials. The major impact was observed within the Pre-BII and memory subtypes, which had a significantly inferior prognosis compared with other subtypes. A multiple Cox proportional hazard analysis documented that BAGS subtypes added significant, independent prognostic information to the translocations and cyclin D classification. BAGS subtype analysis of patient cases identified transcriptional differences, including a number of differentially spliced genes. We identified subtype differences in myeloma at diagnosis, with prognostic impact and predictive potential, supporting an acquired B-cell trait and phenotypic plasticity as a pathogenetic hallmark of MM

Estimating the loss of lifetime function using flexible parametric relative survival models

Abstract Background Within cancer care, dynamic evaluations of the loss in expectation of life provides useful information to patients as well as physicians. The loss of lifetime function yields the conditional loss in expectation of life given survival up to a specific time point. Due to the inevitable censoring in time-to-event data, loss of lifetime estimation requires extrapolation of both the patient and general population survival function. In this context, the accuracy of different extrapolation approaches has not previously been evaluated. Methods The loss of lifetime function was computed by decomposing the all-cause survival function using the relative and general population survival function. To allow extrapolation, the relative survival function was fitted using existing parametric relative survival models. In addition, we introduced a novel mixture cure model suitable for extrapolation. The accuracy of the estimated loss of lifetime function using various extrapolation approaches was assessed in a simulation study and by data from the Danish Cancer Registry where complete follow-up was available. In addition, we illustrated the proposed methodology by analyzing recent data from the Danish Lymphoma Registry. Results No uniformly superior extrapolation method was found, but flexible parametric mixture cure models and flexible parametric relative survival models seemed to be suitable in various scenarios. Conclusion Using extrapolation to estimate the loss of lifetime function requires careful consideration of the relative survival function outside the available follow-up period. We propose extensive sensitivity analyses when estimating the loss of lifetime function

Predictive Value of PET Response Combined with Baseline Metabolic Tumor Volume in Peripheral T-Cell Lymphoma Patients.

Peripheral T-cell lymphoma (PTCL) is a heterogeneous group of aggressive non-Hodgkin lymphomas with poor outcomes on current therapy. We investigated whether response assessed with PET/CT combined with baseline total metabolic tumor volume (TMTV) could detect early relapse or refractory disease. Methods: From 7 European centers, 140 patients with nodal PTCL who underwent baseline PET/CT were selected. Forty-three had interim PET (iPET) performed after 2 cycles (iPET2), 95 had iPET performed after 3 or 4 cycles (iPET3/4), and 96 had end-of-treatment PET (eotPET). Baseline TMTV was computed with a 41% SUV <sub>max</sub> threshold, and PET response was reported using the Deauville 5-point scale. Results: With a median of 43 mo of follow-up, the 2-y progression-free survival (PFS) and overall survival (OS) were 51% and 67%, respectively. iPET2-positive patients (Deauville score ≥ 4) had a significantly worse outcome than iPET2-negative patients (P < 0.0001, hazard ratio of 6.8 for PFS; P < 0.0001, hazard ratio of 6.6 for OS). The value of iPET3/4 was also confirmed for PFS (P < 0.0001) and OS (P < 0.0001). The 2-y PFS and OS for iPET3/4-positive (n = 28) and iPET3/4-negative (n = 67) patients were 16% and 32% versus 75% and 85%, respectively. The eotPET results also reflected patient outcome. A model combining TMTV and iPET3/4 stratified the population into distinct risk groups (TMTV ≤ 230 cm <sup>3</sup> and iPET3/4-negative [2-y PFS/OS, 79%/85%]; TMTV > 230 cm <sup>3</sup> and iPET3/4-negative [59%/84%]; TMTV ≤ 230 cm <sup>3</sup> and iPET3/4-positive [42%/50%]; TMTV > 230 cm <sup>3</sup> and iPET3/4-positive [0%/18%]). Conclusion: iPET response is predictive of outcome and allows early detection of high-risk PTCL patients. Combining iPET with TMTV improves risk stratification in individual patients