Dataset Information

A Clinical Prognostic Model Based on Machine Learning from the Fondazione Italiana Linfomi (FIL) MCL0208 Phase III Trial.

ABSTRACT:

Background

Multicenter clinical trials are producing growing amounts of clinical data. Machine Learning (ML) might facilitate the discovery of novel tools for prognostication and disease-stratification. Taking advantage of a systematic collection of multiple variables, we developed a model derived from data collected on 300 patients with mantle cell lymphoma (MCL) from the Fondazione Italiana Linfomi-MCL0208 phase III trial (NCT02354313).

Methods

We developed a score with a clustering algorithm applied to clinical variables. The candidate score was correlated to overall survival (OS) and validated in two independent data series from the European MCL Network (NCT00209222, NCT00209209); Results: Three groups of patients were significantly discriminated: Low, Intermediate (Int), and High risk (High). Seven discriminants were identified by a feature reduction approach: albumin, Ki-67, lactate dehydrogenase, lymphocytes, platelets, bone marrow infiltration, and B-symptoms. Accordingly, patients in the Int and High groups had shorter OS rates than those in the Low and Int groups, respectively (Int→Low, HR: 3.1, 95% CI: 1.0-9.6; High→Int, HR: 2.3, 95% CI: 1.5-4.7). Based on the 7 markers, we defined the engineered MCL international prognostic index (eMIPI), which was validated and confirmed in two independent cohorts; Conclusions: We developed and validated a ML-based prognostic model for MCL. Even when currently limited to baseline predictors, our approach has high scalability potential.

SUBMITTER: Zaccaria GM

PROVIDER: S-EPMC8750124 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:AIM:Advances in therapy have resulted in improved cure rates and an increasing number of long-term Hodgkin's lymphoma (HL) survivors. However, radiotherapy (RT)-related late effects are still a significant issue, particularly for younger patients with mediastinal disease (secondary cancers, heart diseases). In many Centers, technological evolution has substantially changed RT planning and delivery. This consensus document aims to analyze the current knowledge of Intensity-Modulated Radiation Therapy (IMRT) and Image-Guided Radiation Therapy (IGRT) for mediastinal HL and formulate practical recommendations based on scientific evidence and expert opinions. METHODS:A dedicated working group was set up within the Fondazione Italiana Linfomi (FIL) Radiotherapy Committee in May 2018. After a first meeting, the group adopted a dedicated platform to share retrieved articles and other material. Two group coordinators redacted a first document draft, that was further discussed and finalized in two subsequent meetings. Topics of interest were: 1) Published data comparing 3D-conformal radiotherapy (3D-CRT) and IMRT 2) dose objectives for the organs at risk 3) IGRT protocols and motion management. RESULTS:Data review showed that IMRT might allow for an essential reduction in the high-dose regions for all different thoracic OAR. As very few studies included specific dose constraints for lungs and breasts, the low-dose component for these OAR resulted slightly higher with IMRT vs. 3D-CRT, depending on the technique used. We propose a set of dose objectives for the heart, breasts, lungs, and thyroid. The use of IGRT is advised for margin reduction without specific indications, such as the use of breath-holding techniques. An individual approach, including comparative planning and considering different risk factors for late morbidity, is recommended for each patient. CONCLUSIONS:As HL therapy continues to evolve, with an emphasis on treatment reduction, radiation oncologists should use at best all the available tools to minimize the dose to organs at risk and optimize treatment plans. This document provides indications on the use of IMRT/IGRT based on expert consensus, providing a basis for clinical implementation and future development.

Project description:The increase of lymphoma patient survival led to a modification of the incidence of long-term sequelae, including second malignancies (SM). Several groups have dealt with the incidence of SM, according to the primary treatment; however, a standardized approach for the early detection and screening of SM in the population of lymphoma survivors should be implemented. A systematic review was conducted by Fondazione Italiana Linfomi (FIL), in order to define the incidence of SM, the impact of modern radiotherapy on SM risk, and the usefulness of tailored follow-up and screening strategies for early diagnosis of SM. Classical Hodgkin lymphoma (cHL) and diffuse large B-cell lymphoma (DLBCL) survivors were investigated. The MEDLINE, Embase, and Cochrane Library databases were checked for relevant reports published up to January 2020. The selection process was reported according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. A total of 27 full-text manuscripts resulted as eligible for the analysis. The incidence of SM in cHL patients treated with ABVD was higher compared to the general population and was even higher in patients treated with intensified regimens. The risk increased over time, as well as after 10-15 years from therapy, and was augmented by radiotherapy exposure. In DLBCL, more intensive regimens (i.e., R-CHOEP or R-MegaCHOEP) vs. R-CHOP were associated with a higher SM incidence. Salvage chemotherapy and autologous stem cell transplants increased the risk of SM in both cHL and DLBCL cohorts. A lower incidence of SM, particularly of breast cancer (BC), was shown in cohorts of cHL survivors treated with reduced radiation volumes and doses (involved fields vs. extended fields), but robust trials are still lacking. Considering the advantage of a structured screening for early detection of SM, all the included studies regarded cHL survivors and screening strategy for early BC detection. Moreover, the authors discuss additional papers, to guide the early diagnosis of lung, colorectal, skin, and thyroid cancer in patients at risk due to family history, drug or RT exposure, or unhealthy lifestyles. These screening strategies all passed through patient awareness. A modern approach to chemotherapy and radiotherapy led to a lower risk of SM, which should be confirmed over time. Early detection of secondary cancers could be achieved through a tailored screening program, according to the individual risk profile.

Dataset Information

A Clinical Prognostic Model Based on Machine Learning from the Fondazione Italiana Linfomi (FIL) MCL0208 Phase III Trial.

Background

Methods

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