Dataset Information

A New Prognostic Index for Extranodal Natural Killer/T-Cell Lymphoma:Incorporation of Serum β-2 Microglobulin to PINK.

ABSTRACT:

Purpose

Prognostic Index for Natural Killer Lymphoma (PINK) is the most widely accepted prognostic model for patients withextranodal natural killer/T-cell lymphoma (ENKTL) treated with non-anthracycline-based therapy. We aimed to evaluate the prognostic implications of serum β-2 microglobulin (β2M) in the context of PINK and proposed a new prognostic model.

Materials and methods

A total of 138 patients who were newly diagnosed with ENKTL and treated with non-anthracycline-based chemotherapy were identified. The cut-off value of high serum β2M was calculated by maximal-chi square methods (4.1 mg/L). A new prognostic model incorporating serum β2M into PINK was proposed and validated in an independent validation cohort (n=88).

Results

The patients' median age was 53.5 years (range, 19 to 80 years). Patients with high serum β2M levels had significantly worse overall survival (OS) and progression-free survival (PFS). In multivariate analysis, high serum β2M was an independent adverse prognostic factor for OS. A new PINK-B (Prognostic Index for Natural Killer Lymphoma-serum β-2 microglobulin) model stratifiedpatients into three groups with distinct OS and PFS in the training cohort (3-year OS, 84.1% [95% confidence interval, 75.1 to 94.2], 46.8% [36.1 to 60.8] and 17.6% [6.3 to 49.2] for the low-, intermediate, and high-risk groups, respectively; 3-year PFS, 70.6% [59.4 to 83.8], 35.9% [25.9 to 49.8], and 7.35% [1.1 to 46.7] for the low-, intermediate-, and high-risk groups, respectively). The PINK-B model was further validated in an independent cohort.

Conclusion

Serum β2M is an independent prognostic factor for ENKTL patients. The new serum β2M-based prognostic model may be useful for identifying ultra-high-risk patients, and it can easily be adopted into daily clinical practice.

SUBMITTER: Kang S

PROVIDER: S-EPMC9873344 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Publications

A New Prognostic Index for Extranodal Natural Killer/T-Cell Lymphoma:Incorporation of Serum β-2 Microglobulin to PINK.

Kang Sora S Cho Hyungwoo H Kim Shin S Lee Kyoungmin K Kang Eun Hee EH Park Jung Sun JS Lee Yoon Sei YS Park Chan-Sik CS Go Heounjeong H Huh Jooryung J Ryu Jin Sook JS Lee Sang-Wook SW Kim Seok Jin SJ Kim Won Seog WS Yoon Sang Eun SE Ko Young Hyeh YH Suh Cheolwon C

Cancer research and treatment 20220331 1

<h4>Purpose</h4>Prognostic Index for Natural Killer Lymphoma (PINK) is the most widely accepted prognostic model for patients withextranodal natural killer/T-cell lymphoma (ENKTL) treated with non-anthracycline-based therapy. We aimed to evaluate the prognostic implications of serum β-2 microglobulin (β2M) in the context of PINK and proposed a new prognostic model.<h4>Materials and methods</h4>A total of 138 patients who were newly diagnosed with ENKTL and treated with non-anthracycline-based ch ...[more]

PMID: 35381163

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Project description:BackgroundExtranodal natural killer (NK)/T-cell lymphoma (ENKTCL) is an aggressive lymphoma with marked heterogeneity, resulting in a distinct prognosis even in patients with the same disease stage. The nomogram-revised risk index (NRI) has been proposed to stratify patients with ENKTCL. Numerous reports have revealed the prognostic role of serum ferritin in various cancers.PurposeWe aimed to evaluate the role of NRI in our single cohort of patients with ENKTCL treated uniformly, explore the prognostic value of ferritin, and establish a new prognostic model to better stratify patients with ENKTCL.MethodsWe included 326 patients with ENKTCL with detailed data regarding clinical characteristics and survival outcomes. All patients were treated with asparaginase-based chemotherapy with or without radiotherapy. Multiple R packages were used to analyze the prognostic factors and derive a novel prognostic model.ResultsIn the training cohort comprising 236 patients with ENKTCL, NRI significantly correlated with progression-free survival (PFS) and overall survival (p < 0.0001). Using a ferritin level of 400 μg/L as the cutoff value, patients with high ferritin levels had significantly inferior PFS (p = 0.00028). Integrating the NRI score and four easily accessible clinical parameters, namely ferritin, hemoglobin, albumin, and D-dimer, a new prognostic model was constructed, stratifying patients with ENKTCL into three risk groups. This new prognostic model was independent of disease stage and NRI and performed better than NRI. Furthermore, this model helped to stratify patients within the same NRI risk groups. Finally, the role of this novel prognostic model was validated in the external validation cohort comprising 90 patients with ENKTCL.ConclusionsSerum ferritin level could be a novel prognostic factor in patients with ENKTCL. The new prognostic model combining NRI and clinical parameters could better predict the prognosis of ENKTCL, thereby warranting further validation and potentially guiding individualized treatment in future prospective clinical trials.

Project description:BackgroundThe prognostic index of natural killer lymphoma (PINK) is recommended for use as a prognostic model for determining the best non-anthracycline-based treatment for extranodal natural killer T-cell lymphoma, nasal-type (ENKTL). However, this model does not provide an accurate individual risk estimation for patients; therefore, our retrospective study was conducted to determine this risk.MethodsClinical data from 250 patients with ENKTL treated with non-anthracycline-based regimens were analyzed. The statistically significant clinical characteristics were selected as the parameters for our models. The patient data from 250 patients were randomly divided into 5 groups for 5-fold cross validation before final models were established on all of the patients' data. A statistical model nomogram based on a Cox proportional hazards model, and a machine learning model based on the lightGBM algorithm, were constructed. Concordance index (C-index) and calibration curve, areas under the curve (AUC) values, and binary error were used to evaluate two models.ResultsFive variables [age, the Chinese Southwest Oncology Group and Asia Lymphoma Study Group ENKTL (CA) staging system, Eastern Cooperative Oncology Group (ECOG) score, B symptoms, and lactate dehydrogenase (LDH)] were significant and were selected as parameters for creating the statistical model nomogram, while lesion sites (anatomical regions, lymph nodes and primary lesion site) took place of CA staging system in machine learning model. During cross validation, the mean C-indices of training cohort and validation cohort for statistical model nomogram and PINK were 0.851±0.008, 0.843±0.029, 0.758±0.019 and 0.757±0.080, respectively, while the mean 3-year AUC for machine learning model were 0.920±0.010 and 0.865±0.035, respectively. The calibration curves and binary errors showed a good correlation between the predicted result and the reality.ConclusionsThese two models could provide ENKTL patients with an accurate individual risk estimation in the era of non-anthracycline-based treatment.

Dataset Information

A New Prognostic Index for Extranodal Natural Killer/T-Cell Lymphoma:Incorporation of Serum β-2 Microglobulin to PINK.

Purpose

Materials and methods

Results

Conclusion

Publications

A New Prognostic Index for Extranodal Natural Killer/T-Cell Lymphoma:Incorporation of Serum β-2 Microglobulin to PINK.

Similar Datasets

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