Prognostic Nomogram and Predictive Factors in Refractory or Relapsed Diffuse Large B-Cell Lymphoma Patients Failing Front-Line R-CHOP Regimens

Establishment of Prognosis Nomogram for Primary Splenic Diffuse Large B Cell Lymphoma: A Study Based on SEER Database

Despite being the most common primary tumor of the spleen, in the past, few studies have predicted the prognosis of primary spleen diffuse large B cell lymphoma. This study aimed to establish a nomogram prediction model of overall survival in primary DLBCL of the spleen. We screened out 347 patients with primary splenic DLBCL from surveillance, epidemiology, and end results database. According to the Cox regression results (age, Ann Arbor Stage, splenectomy and chemotherapy was the independent risk factor for primary splenic DLBCL), the nomogram was constructed. We evaluated the predictive ability of nomogram with C-Index (training cohort: 0.719 [0.669-0.769]; validation cohort: 0.711 [0.641-0.781]) and 3-year/5-year receiver operating characteristic area under curve (3-year/5-year ROCAUC, training cohort: 0.731/0.742; validation cohort: 0.721/0.742). Calibratioin plot shows that our predicted values fluctuate around the actual value, indicating good agreement with nomogram. The decision curve analysis (DCA) results showed that our nomogram could benefit more than Ann Arbor Stage for predicts the prognosis of the primary splenic DLBCL. The Kaplan-Meier and landmark analysis showed that a great discrimination between high-risk group and low-risk group (P < 0.05) and indicating that our nomogram has the good ability to identify high-risk patients. In this study, a nomogram prediction model for primary spleen DLBCL was established, which has good ability of prediction and generalization. It can help clinicians carry out individualized treatment measures.

A new prognostic nomogram in patients with mucosa-associated lymphoid tissue lymphoma: a multicenter retrospective study

Background

The present study sought to understand how clinical factors and inflammatory biomarkers affected the prognosis of mucosa-associated lymphoid tissue (MALT) lymphoma and develop a predictive nomogram to assist in clinical practice.

Methods

We conducted a retrospective study on 183 cases of newly diagnosed MALT lymphoma from January 2011 to October 2021, randomly divided into two groups: a training cohort (75%); and a validation cohort (25%). The least absolute shrinkage and selection operator (LASSO) regression analysis was combined with multivariate Cox regression analysis to construct a nomogram for predicting the progression-free survival (PFS) in patients with MALT lymphoma. To evaluate the accuracy of the nomogram model, the area under the receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were used.

Results

The PFS was significantly associated with the Ann Arbor Stage, targeted therapy, radiotherapy, and platelet-to-lymphocyte ratio (PLR) in MALT lymphoma. These four variables were combined to establish a nomogram to predict the PFS rates at three and five years. Importantly, our nomogram yielded good predictive value with area under the ROC curve (AUC) values of 0.841 and 0.763 in the training cohort and 0.860 and 0.879 in the validation cohort for the 3-year and 5-year PFS, respectively. Furthermore, the 3-year and 5-year PFS calibration curves revealed a high degree of consistency between the prediction and the actual probability of relapse. Additionally, DCA demonstrated the net clinical benefit of this nomogram and its ability to identify high-risk patients accurately.

Conclusion

The new nomogram model could accurately predict the prognosis of MALT lymphoma patients and assist clinicians in designing individualized treatments.

A New Staging System Based on the Dynamic Prognostic Nomogram for Elderly Patients With Primary Gastrointestinal Diffuse Large B-Cell Lymphoma

Objective

The purpose of this study is to establish an accurate prognostic model based on important clinical parameters to predict the overall survival (OS) of elderly patients with primary gastrointestinal diffuse large B-cell lymphoma (EGI DLBCL).

Methods

The Cox regression analysis is based on data from the Surveillance, Epidemiology, and End Results (SEER) database.

Results

A total of 1,783 EGI DLBCL cases were eligible for the study [median (interquartile range, IQR) age, 75 (68–82) years; 974 (54.63%) males], of which 1,248 were randomly assigned to the development cohort, while 535 were into the validation cohort. A more accurate and convenient dynamic prognostic nomogram based on age, stage, radiation, and chemotherapy was developed and validated, of which the predictive performance was superior to that of the Ann Arbor staging system [C-index:0.69 (95% CI:0.67–0.71) vs. 56 (95%CI:0.54–0.58); P < 0.001]. The 3- and 5-year AUC values of ROC curves for 3-year OS and 5-year OS in the development cohort and the validation cohort were were alll above 0.7.

Conclusion

We establish and validate a more accurate and convenient dynamic prognostic nomogram for patients with EGI DLBCL, which can provide evidence for individual treatment and follow-up.

Development and External Validation of a Nomogram to Predict Cancer-Specific Survival in Patients with Primary Intestinal Non-Hodgkin Lymphomas

Purpose

Primary intestinal non-Hodgkin lymphoma (PINHL) is a biologically and clinically heterogeneous disease. Few individual prediction models are available to establish prognoses for PINHL patients. Herein, a novel nomogram was developed and verified to predict long-term cancer-specific survival (CSS) rates in PINHL patients, and a convenient online risk calculator was created using the nomogram.

Materials and Methods

Data on PINHL patients from January 1, 2004, to December 31, 2015, obtained from the Surveillance, Epidemiology, and End Results (SEER) database (n = 2372; training cohort), were analyzed by Cox regression to identify independent prognostic parameters for CSS. The nomogram was internally and externally validated in a SEER cohort (n = 1014) and a First Affiliated Hospital of Guangzhou University of Chinese Medicine (FAHGUCM) cohort (n = 37), respectively. Area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA) were used to evaluate nomogram performance.

Results

Five independent predictors were identified, namely, age, marital status, Ann Arbor Stage, B symptoms, and histologic type. The nomogram showed good performance in discrimination and calibration, with C-indices of 0.772 (95% CI: 0.754–0.790), 0.763 (95% CI: 0.734–0.792), and 0.851 (95% CI: 0.755–0.947) in the training, internal validation, and external validation cohorts, respectively. The calibration curve indicated that the nomogram was accurate, and DCA showed that the nomogram had a high clinical application value. AUC values indicated that the prediction accuracy of the nomogram was higher than that of Ann Arbor Stage (training cohort: 0.804 vs 0.630; internal validation cohort: 0.800 vs 0.637; external validation cohort: 0.811 vs 0.598), and Kaplan–Meier curves indicated the same.

Conclusion

A nomogram was developed to assist clinicians in predicting the survival of PINHL patients and in making optimal treatment decisions. An online calculator based on the nomogram was made available at https://cuifenzhang.shinyapps.io/DynNomapp/.

Outcomes of Diffuse Large B-Cell Non-Hodgkin's Lymphoma After Gemcitabine-Based Second Salvage Chemotherapy: A Single-Center Study

Background Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin's lymphoma with a five-year survival of 60%-70% with chemoimmunotherapy consisting of the R-CHOP combination (rituximab, cyclophosphamide, vincristine, doxorubicin, and prednisone), with a relapse/refractory rate of 20-50%. Salvage therapy with HDT-ASCT is the treatment of choice for patients with relapsed/refractory disease with a success rate of 50%-60%. Patients who do not respond to the first salvage regimen or who relapsed after the first salvage regimen, with or without high-dose chemotherapy (HDT)-autologous stem cell transplantation (ASCT), have poor overall responses and survival and should be offered novel therapies. The objective of our study was to evaluate responses to second salvage, gemcitabine-based therapy with or without HDT-ASCT in a resource-limited setting. Materials and methods This was a retrospective study, including 55 patients aged >18 years, diagnosed with DLBCL and having received gemcitabine-based second salvage chemotherapy. Results The median age was 34 years, only one patient achieved progression-free survival (PFS) of >12 months with ORR of 27% to two cycles of gemcitabine-based combination, two years PFS and OS of 9.6% and 34%, respectively, and a median PFS and OS of four months and 13 months, respectively. Conclusion DLBCL patients, refractory to first-line and first salvage chemotherapy, should be considered for novel therapies or opt for palliative care rather than second salvage chemotherapy and HDT-ASCT, which results in poor overall response and significant toxicities.

Development and Validation of a Novel Risk Stratification Model for Cancer-Specific Survival in Diffuse Large B-Cell Lymphoma

Diffuse large B-cell lymphoma (DLBCL) is a biologically and clinically heterogenous disease. Identifying more precise and individual survival prognostic models are still needed. This study aimed to develop a predictive nomogram and a web-based survival rate calculator that can dynamically predict the long-term cancer-specific survival (CSS) of DLBCL patients. A total of 3,573 eligible patients with DLBCL from 2004 to 2015 were extracted from the Surveillance, Epidemiology and End Results (SEER) database. The entire group was randomly divided into the training (n = 2,504) and validation (n = 1,069) cohorts. We identified six independent predictors for survival including age, sex, marital status, Ann Arbor stage, B symptom, and chemotherapy, which were used to construct the nomogram and the web-based survival rate calculator. The C-index of the nomogram was 0.709 (95% CI, 0.692–0.726) in the training cohort and 0.700 (95% CI, 0.671–0.729) in the validation cohort. The AUC values of the nomogram for predicting the 1-, 5-, and 10- year CSS rates ranged from 0.704 to 0.765 in both cohorts. All calibration curves revealed optimal consistency between predicted and actual survival. A risk stratification model generated based on the nomogram showed a favorable level of predictive accuracy compared with the IPI, R-IPI, and Ann Arbor stage in both cohorts according to the AUC values (training cohort: 0.715 vs 0.676, 0.652, and 0.648; validation cohort: 0.695 vs 0.692, 0.657, and 0.624) and K-M survival curves. In conclusion, we have established and validated a novel nomogram risk stratification model and a web-based survival rate calculator that can dynamically predict the long-term CSS in DLBCL, which revealed more discriminative and predictive accuracy than the IPI, R-IPI, and Ann Arbor stage in the rituximab era.

A novel nomogram to predict early neurological deterioration in patients with acute ischaemic stroke

BACKGROUND AND PURPOSE

Acute ischaemic stroke (AIS) is a vital cause of mortality and morbidity in China. Many AIS patients develop early neurological deterioration (END). This study aimed to construct a nomogram to predict END in AIS patients.

METHODS

Acute ischaemic stroke patients in Nanjing First Hospital were recruited as the training cohort. Additional patients in Nantong Third People's Hospital were enrolled as the validation cohort. Multivariate logistic regression was utilized to establish the nomogram. Discrimination and calibration performance of the nomogram were tested by concordance index and calibration plots. Decision curve analysis was employed to assess the utility of the nomogram.

RESULTS

In all, 1889 and 818 patients were recruited in the training and validation cohorts, respectively. Age [odds ratio (OR) 1.075; 95% confidence interval (CI) 1.059-1.091], diabetes mellitus (OR 1.673; 95% CI 1.181-2.370), atrial fibrillation (OR 3.297; 95% CI 2.005-5.421), previous antiplatelet medication (OR 0.473; 95% CI 0.301-0.744), hyper-sensitive C-reactive protein (OR 1.049; 95% CI 1.036-1.063) and baseline National Institutes of Health Stroke Scale (OR 1.071; 95% CI 1.045-1.098) were associated with END and incorporated in the nomogram. The concordance index was 0.826 (95% CI 0.785-0.885) and 0.798 (95% CI 0.749-0.847) in the training and validation cohorts. By decision curve analysis, the model was relevant between thresholds of 0.06 and 0.90 in the training cohort and 0.08 and 0.77 in the validation cohort.

CONCLUSIONS

The nomogram composed of hyper-sensitive C-reactive protein, age, diabetes mellitus, atrial fibrillation, previous antiplatelet medication and baseline National Institutes of Health Stroke Scale may predict the risk of END in AIS patients.