Prognostic factors in primary central nervous system lymphoma

Morales-Martínez, Andrea; Nichelli, Lucia; Hernández-Verdin, Isaias; Houillier, Caroline; Alentorn, Agustí; Hoang-Xuân, Khê

doi:10.1097/cco.0000000000000896

Cited by 7 publications

(3 citation statements)

References 111 publications

(160 reference statements)

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“…A MMSE < 27 was associated with a poor prognosis for patients younger than 70 years-old in a phase 3 study [29] while a MMSE < 25 was correlated to a poor survival for PCSNL older than 60 years in a phase 2 study [30]. A large number of biomarkers have shown their interest or are still being studied to assess their prognostic impact, including biomarkers in cerebrospinal fluid and neuroimaging data [31 ▪ ,32 ▪ ].…”

Section: Prognosis Factor Of Primary Central Nervous System Lymphomamentioning

confidence: 99%

Primary central nervous system lymphoma (PCNSL) in older patients

Bertucci

Harlay

Chinot

et al. 2023

Current Opinion in Oncology

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Introduction Primary central nervous system lymphoma (PCNSL) is a rare, chemo and radio-sensitive tumor limited to the central nervous system. The incidence of PCSNL increases notably in the elderly population which represented approximately half of the patients. The limit of ‘elderly’ population remained debated and nonuniform, including 60 years as a cutoff for brain radiotherapy, 65 years for autologous stem-cell transplantation, and 70 years for the last clinical trials. Current therapeutic options include first line treatment based on high-dose methotrexate based polychemotherapy, consolidation chemotherapy, and adapted autologous stem cell transplantation for highly selected patients. At relapse, single agent targeted therapies or salvage chemotherapy followed by intensive consolidation are promising therapeutic options. Nevertheless, improving management of elderly patients is an urgent medical need that currently remains unresolved. Objective We will focus on elderly patients with PCNSL and their specificities including clinical presentations, available therapeutic options and adaptations to be made. Conclusion To improve survival, it will be necessary to personalized and adapt the treatments, to each patient and his comorbidities, to increase their effectiveness and limit their toxicity in this frail population. Finally, inclusion of these patients in clinical trials is one of the major challenges to significantly change PCNSL elderly patient prognosis.

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Section: Prognosis Factor Of Primary Central Nervous System Lymphomamentioning

confidence: 99%

Primary central nervous system lymphoma (PCNSL) in older patients

Bertucci

Harlay

Chinot

et al. 2023

Current Opinion in Oncology

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“…In a population-based study by the French oculocerebral lymphoma network, PCNSL patients (n = 1002) treated according to current national guidelines had a median overall survival (OS) of 25 months and a 5-year survival rate of 38% [10] . Age is the main independent prognostic factor for PCNSL with better prognoses in younger patients: the 5-year progression-free survival rates were 61% and 28% in patients under or above the age of 60 years, respectively [11] . This suggests that clinicians should consider the impact of age on prognosis when choosing the optimal treatment for PCNSL patients.…”

Section: Introductionmentioning

confidence: 99%

Age-related differences in primary central nervous system lymphomas based on the SEER database

Wang,

Zheng,

Liang

et al. 2023

Preprint

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Objective: The aim of this study was to compare prognostic factors and survival outcomes in patients with primary central nervous system lymphoma (PCNSL) stratified according to age (younger vs older than 60 years of age). Methods: The Surveillance, Epidemiology, and End Results (SEER) database was queried for all patients diagnosed with PCNSL between 2000 and 2019. Clinical parameters were collected, and patients were stratified and compared according to age. Results: Between 2000 and 2019, a total of 5812 patients were diagnosed with PCNSL, of whom 2175 (37%) were ≤ 60 years old and 3637 (63%) were > 60 years old, hereafter referred to as “younger” and “older” patients, respectively. The younger patients had a higher rate of being diagnosed with stage I–II PCNSL (64% vs 60%), a higher rate of receiving chemotherapy (68% vs 63%), a higher rate of receiving radiotherapy (34% vs 26%, P < 0.001), a similar rate of receiving surgery, and a longer survival time. The most common histological subtype among PCNSL patients was diffuse large B-cell lymphoma (DLBCL) (PCNS-DLBCL; n = 4458, 77%). Multifactorial Cox regression analysis showed that younger PCNS-DLBCL patients who received surgery and chemotherapy exhibited significantly improved overall survival (OS) and disease-specific mortality (DSM) and that African American patients were associated with poorer OS and DSM. Older patients receiving surgery, chemotherapy, and radiotherapy exhibited significantly improved OS and DSM, and male sex and higher Ann Arbor stage were associated with poorer OS and DSM. We created a nomogram for PCNS-DLBCL to predict OS, with a C-index of 0.6749 (95% confidence interval: 0.6641–0.6857) in the younger cohort and 0.6676 (95% confidence interval: 0.6595–0.6759) in the older cohort, indicating that the nomogram had good predictive value. In the combined therapy analysis, chemotherapy combined with surgical resection had better OS and DSM in all patients. Conclusions: The two age-stratified cohorts significantly differed in terms of OS and independent influences on OS and DSM. However, chemotherapy combined with surgical resection resulted in better OS and DSM in all patients. Our constructed nomogram exhibited high accuracy in predicting OS in PCNS-DLBCL patients.

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“…Primary Central Nervous System Lymphoma (PCNSL) constitutes a distinct subset of lymphoma, representing 4% of all cerebral malignancies. Its prognosis is notably poorer and mortality rate signi cantly higher when compared to other lymphoma subtypes [1][2][3] [4]. The prevalence of PCNSL has been on an upward trajectory in recent years, a trend partially attributable to the global aging population [3] [5].…”

Section: Introductionmentioning

confidence: 99%

Automatic segmentation model of primary central nervous system lymphoma based on multiple sequences of magnetic resonance images using deep learning

Lu,

Zhou,

Zhao

et al. 2023

Preprint

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Purpose and Background. Accurate quantitative assessment of PCNSL by gadolinum-contrast Magnetic resonance imaging (MRI) is closely related to therapy planning, surveillance and prognosis, However, precise volume assessment by manual segmentation is time-consuming and subject to high intra- and interrater variabilities by imaging readers, with poor consistency. In order to solve this problem, we constructed a multimodal artificial intelligence deep learning segmentation model based on multi-sequence MRI images of patients with PCNSL and identified its efficiency, so as to quantitatively calculate volume and other indicators, and compare the consistency and accuracy with doctors' labeling methods. Materials and Methods. A total of 41 PCNSL patients from six Chinese medical centers with pathologically confirmed PCNSL were analyzed. Region of interest (ROI) was manually segmented on contrast-enhanced T1-weighted and T2 scans. Fully automated voxelwise segmentation of tumor components was performed using a 3D convolutional neural network (DeepMedic) trained on gliomas (n = 220). deep-learning model (DLM) segmentations were compared to manual segmentations performed in a 3D voxelwise manner by two readers (radiologist and neurosurgeon; consensus reading) from T1 CE and FLAIR, which served as the reference standard. The Dice similarity coefficient (DSC) were used to evaluate the performance of the models. Successful detection of PCNSL was defined if the DLM obtained a spatial overlap with the manual segmentation of the tumor core (at least one voxel, DSC >0). Mann-Whitney U test was applied to compare continuous variables, while chi-squared test was used for categorical variables between groups. A two-tailed P value <0.05 indicated statistical significance. Results. The DLM detected 66 of 69 PCNSL, representing a sensitivity of 95.7%. Compared to the reference standard, DLM achieved good spatial overlap for total tumor volume (TTV, union of tumor volume in T1 CE and FLAIR; average size 77.16 ± 62.4 cm3, median DSC: 0.76) and tumor core (contrast enhancing tumor in T1 CE; average size: 11.67 ± 13.88 cm3, median DSC: 0.73). High volumetric correlation between automated and manual segmentations was observed (TTV: r= 0.88, P < 0.0001; core: r = 0.86, P < 0.0001). Performance of automated segmentations was comparable between pre-treatment and follow-up scans without significant differences (TTV: P = 0.242, core: P = 0.177). Conclusion. Compared to manual segmentation on routine clinical MRI images, our automatic segmentation model of PCNSL based on multiple sequences of MRI images displayed comparable segmentation in both pretherapy and the process of the treatment, despite the complex and multifaceted appearance of this lymphoma subtype , implying its immense potential to be used in the whole follow-up monitoring process of PCNSL.

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Prognostic factors in primary central nervous system lymphoma

Cited by 7 publications

References 111 publications

Primary central nervous system lymphoma (PCNSL) in older patients

Primary central nervous system lymphoma (PCNSL) in older patients

Age-related differences in primary central nervous system lymphomas based on the SEER database

Automatic segmentation model of primary central nervous system lymphoma based on multiple sequences of magnetic resonance images using deep learning

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