scholarly journals Proposal of New Prognostic Index for Patients with Diffuse Large B-Cell Lymphoma in the Rituximab Era

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 1668-1668
Author(s):  
Shinkyo Yoon ◽  
Dok Hyun Yoon ◽  
Shin Kim ◽  
Kyoungmin Lee ◽  
Eun Hee Kang ◽  
...  
Keyword(s):  
Prognostic Model ◽  
Medical Center ◽  
Prognostic Index ◽  
P Value ◽  
Training Set ◽  
Internal Validation ◽  
Index Model ◽  
Asan Medical ◽  
Baseline Characteristics ◽  
Validation Set

Abstract Background The International Prognostic Index (IPI) has been useful prognostic tool to predict prognosis of aggressive non-Hodgkin lymphoma in the last 20 years. Since the advent of R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) chemotherapy for diffuse large B-cell lymphoma (DLBCL), its utility has been challenged and other prognostic index including revised IPI and National Comprehensive Cancer Network (NCCN)-IPI were proposed, which are not popularly used yet. We aimed to develop new prognostic model for DLBCL in rituximab era. Method Between March 2004 and June 2012, patients with DLBCL treated with R-CHOP were identified in the database of the Asan Medical Center (AMC) Lymphoma Registry. Primary end point was to devise a new prognostic index for DLBCL. Secondary end point was to validate the NCCN-IPI in our cohort. We tested new prognostic index model in the training set of AMC cohort consisted of randomly selected 80% of the sample (503 patients). The remaining 20% (118 patients) was used as an internal validations set. Results The AMC cohort consisted of 621 patients. Median follow-up duration was 43.3 months (6.2-122.5 months). Baseline characteristics of AMC cohort are presented in table 1. Median age was 57 years (range, 16-85 years). Median ϐ-2 microglobulin (ϐ-2 MG) was 2.10 mg/L (range, 1.0-66.0 mg/L). The univariate analysis of baseline characteristics revealed that age (≦60 vs. >60 years), LDH (within normal vs. increased), ECOG performance (0 or 1 vs. ≧2), advanced stage (Ann Arbor stage I/II vs. III/IV), extra-nodal involvement (≦1 vs. >1), B symptoms (no vs. yes), and ϐ-2 MG (≦2.5 vs. >2.5) could predict overall survival (OS), whereas bulky disease and gender did not (p value 0.140, 0.621, respectively). In the multivariate analysis, age, LDH, ECOG performance status, and ϐ-2 MG were significantly associated with OS (p value 0.001, <0.001, 0.004, and 0.019, respectively), while stage, extra-nodal involvement, and B symptom did not (p value 0.057, 0.233, and 0.577, respectively). We developed a new prognostic model with these 4 significant factors in the multivariate analysis. One point is assigned for each of the risk factors without refined categorization. Four risk groups were composed as followings: low (0 point), low-intermediate (1 point), high-intermediate (2-3 points), and high (4 points). The new prognostic model showed better discriminative power compared with classic IPI (Figure 1A). Five-year OS of low- and high-risk subgroup in new scoring model and classic IPI model in AMC cohort were 95% and 32% versus 89% and 45%, respectively. Our model was validated in an internal validation set (Figure 1B). NCCN-IPI also could stratify four risk groups (Figure 1 A and B). Conclusion We propose a new prognostic index model for DLBCL in rituximab era with age, LDH, ECOG performance and ϐ-2 MG, which has good discriminative power and convenient to apply. It warrants further validation using an independent cohort. Table 1. Baseline Characteristics Characteristics Total N=621 % Training set N=503 % Validation set N=118 % Age, years Median, range ≦ 60 years > 60 years 57.0 377 244 16-85 60.7 39.3 57.0 300 203 16-84 59.6 40.4 57.0 77 41 17-85 65.3 34.7 Sex Male Female 343 278 55.2 44.8 273 230 54.3 45.7 70 48 59.3 40.7 ECOG PS 0 or 1 ≧ 2 569 52 91.6 8.4 462 41 91.8 8.2 107 11 90.7 9.3 Serum lactate dehydrogenase levels Normal Elevated 334 287 53.8 46.2 279 224 55.5 44.4 55 63 46.6 53.4 Ann Arbor stage I and II III and IV 293 328 47.2 52.8 236 267 46.9 53.1 57 61 48.3 51.7 Number of extranodal sites <2 ≧ 2 403 218 64.9 35.1 329 174 65.4 34.6 74 44 62.7 37.3 B symptoms No Yes 549 72 88.4 11.6 447 56 88.9 11.1 102 16 86.4 13.6 International prognostic index Low/ low-intermediate High-intermediate/high 404 217 65.1 34.9 327 176 65.0 35.0 77 41 65.3 34.7 ¥Â -2 microglobulin, mg/L Median, range ≦ 2.5 mg/L > 2.5 mg/L 2.1 422 199 1.0-66.0 68.0 32.0 2.1 339 164 1.0-29.6 67.4 32.6 2.1 83 35 1.0-66.0 70.3 28.7 Table 2. Multivariate Analysis for Factors Associated with Overall Survival Factors HR 95% CI P value Score Age, years ≦ 60 years > 60 years 1.000 2.051 1.362-3.090 0.001 1 Serum lactate dehydrogenase levels Normal Elevated 1.000 3.165 1.951-5.135 <0.001 1 ECOG PS 0 or 1 ≧ 2 1.000 2.073 1.261-3.407 0.004 1 ϐ -2 microglobulin, mg/L ≦ 2.5 mg/L > 2.5 mg/L 1.000 1.691 1.0391-2.622 0.019 1 Figure 1. IPI versus NCCN IPI versus new prognostic index model in Asan Medical Center training set (A) and internal validation set (B) Figure 1. IPI versus NCCN IPI versus new prognostic index model in Asan Medical Center training set (A) and internal validation set (B) Disclosures No relevant conflicts of interest to declare.

scholarly journals An Immune-Clinical Prognostic Index (ICPI) for Patients With De Novo Follicular Lymphoma Treated With R-CHOP/CHOP Chemotherapy

2021 ◽  
Vol 11 ◽  
Author(s):  
Yaxiao Lu ◽  
Jingwei Yu ◽  
Wenchen Gong ◽  
Liping Su ◽  
Xiuhua Sun ◽  
...  
Keyword(s):  
De Novo ◽  
External Validation ◽  
Prognostic Index ◽  
Risk Groups ◽  
Chop Chemotherapy ◽  
Training Set ◽  
Chi Square ◽  
T Lymphocyte Subsets ◽  
Internal Validation ◽  
Validation Set

PurposeAlthough the role of tumor-infiltrating T cells in follicular lymphoma (FL) has been reported previously, the prognostic value of peripheral blood T lymphocyte subsets has not been systematically assessed. Thus, we aim to incorporate T-cell subsets with clinical features to develop a predictive model of clinical outcome.MethodsWe retrospectively screened a total of 1,008 patients, including 252 newly diagnosed de novo FL patients with available peripheral blood T lymphocyte subsets who were randomized to different sets (177 in the training set and 75 in the internal validation set). A nomogram and a novel immune-clinical prognostic index (ICPI) were established according to multivariate Cox regression analysis for progression-free survival (PFS). The concordance index (C-index), Akaike’s information criterion (AIC), and likelihood ratio chi-square were employed to compare the ICPI’s discriminatory capability and homogeneity to that of FLIPI, FLIPI2, and PRIMA-PI. Additional external validation was performed using a dataset (n = 157) from other four centers.ResultsIn the training set, multivariate analysis identified five independent prognostic factors (Stage III/IV disease, elevated lactate dehydrogenase (LDH), Hb &lt;120g/L, CD4+ &lt;30.7% and CD8+ &gt;36.6%) for PFS. A novel ICPI was established according to the number of risk factors and stratify patients into 3 risk groups: high, intermediate, and low-risk with 4-5, 2-3, 0-1 risk factors respectively. The hazard ratios for patients in the high and intermediate-risk groups than those in the low-risk were 27.640 and 2.758. The ICPI could stratify patients into different risk groups both in the training set (P &lt; 0.0001), internal validation set (P = 0.0039) and external validation set (P = 0.04). Moreover, in patients treated with RCHOP-like therapy, the ICPI was also predictive (P &lt; 0.0001). In comparison to FLIPI, FLIPI2, and PRIMA-PI (C-index, 0.613-0.647), the ICPI offered adequate discrimination capability with C-index values of 0.679. Additionally, it exhibits good performance based on the lowest AIC and highest likelihood ratio chi-square score.ConclusionsThe ICPI is a novel predictive model with improved prognostic performance for patients with de novo FL treated with R-CHOP/CHOP chemotherapy. It is capable to be used in routine practice and guides individualized precision therapy.

scholarly journals The Engineered MIPI (e-MIPI), a Candidate Data-Mining Based Mantle Cell Lymphoma Prognostic Index Developed from the Dataset of the Fondazione Italiana Linfomi (FIL) MCL0208 Phase III Trial

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 2890-2890
Author(s):  
Gian Maria Zaccaria ◽  
Simone Ferrero ◽  
Roberto Passera ◽  
Andrea Evangelista ◽  
Mariella Loschirico ◽  
...  
Keyword(s):  
Data Mining ◽  
Hierarchical Clustering ◽  
Clustering Analysis ◽  
Prognostic Model ◽  
Prognostic Index ◽  
Large Datasets ◽  
Phase Iii ◽  
Training Set ◽  
Validation Set ◽  
Prognostic Indexes

Abstract Background and aims The amount of clinical and biological data stored within clinical trials is growing exponentially. Data warehousing (DW) is useful for systematic global evaluation of information collected in trials: the highly translational FIL(Fondazione Italiana Linfomi)-MCL0208 trial has been used to test DW to improve data quality and to discover putative associations [Zaccaria, ASH 17]. In this study we developed an engineered prognostic model, focusing on easily accessible clinical variables. For this purpose, we exploited hierarchical clustering with the aim of seeking hidden patterns of interest in large datasets. Hence, these tools allowed to develop a novel prognostic model: the engineered MIPI index (e-MIPI). Herein we present the first results, on baseline clinical characteristics:clustering analysis and definition of a signature of predictive variablesconstruction of the e-MIPI to detect patients' risk of relapsecomparison with known prognostic indexes for MCLvalidation of the signature on independent subset of patients. Methods Data were retrieved from electronic case report forms of the phase III, multicenter FIL-MCL0208 trial (NCT02354313) for younger MCL patients [Cortelazzo, EHA 15]. The study enrolled 300 subjects, with median followup of 51 months. In this work we employed baseline clinical data and May '18 as survival outcomes cut-off. For the present analysis, we started from 32 baseline features: 7 were not eligible due to number of missing values (MVs ≥40). Features with <15 MVs were imputed by median of observations. Secondly, 18 not binary variables were dichotomized, to be compared to the 7 binary ones: normal vs abnormal range or lower vs higher than a recognized cut-off value. Patients were thus split in 2 subsets, training (n=185) and validation (n=115): for the training set, only patients with no MVs were chosen. Clustering analysis was performed to discriminate different groups of patients. Thus, we applied a recursive feature reduction, according to regression modeling, to extrapolate a restricted signature predictive of both progression free survival (PFS) and overall survival (OS). Survival analyses were done according to e-MIPI classes via both multivariate Cox and Kaplan-Maier modeling. Therefore, the e-MIPI classification was compared to known prognostic models [Hoster, Blood 08]. Finally, the signature was tested on the validation set: if any variable of the e-MIPI was missing (MVs=36, 29 and 15 for albumin - alb, Ki67 and flowcytometric peripheral blood invasion - flowpb) data mining (K-nn) technique was employed for imputation. Clustering and statistical analyses were implemented via MATLAB© and SPSS©. Results Training set: the clustering analysis allowed to define 3 groups of subjects: C1 (n=71), C2 (n=77) and C3 (n=37), showing significantly different PFS and OS. Thus, the e-MIPI index was modeled based on a signature of 9 significant features (fig 1): histologic bone marrow infiltration (bminf), flowpb, Ki67, B symptoms, platelets (plts), ldh, white blood cells (wbc), hemoglobin (hb) and alb levels. The re-clustering of the training set according to the e-MIPI confirmed the original patients clustering with 83% of accuracy. Figure 2A depicts the PFS curves stratified for the e-MIPI: C1, C2 and C3 groups have been renamed as low (L), intermediate (I) and high (H) e-MIPI risk classes, respectively. Each comparison reached the statistical significancy: I vs L, p=0.010; H vs I, p=0.023, outperforming in our series both the MIPI-St (H vs I risk, p=0.801) and MIPI-Bio (I vs L risk, p=0.665, fig. 2B) classifications. Validation set: the e-MIPI allowed to discriminate 3 groups of subjects C1 (n=32), C2 (n=59) and C3 (n=24). Actually, the e-MIPI on the validation set (fig. 2C) confirmed the results of the training set, overall improving the MIPI-St stratification (H vs I, p=0.059 ⇒ p=0.049), even if without reaching the statistical significancy on the I vs L comparison (p=0.24 ⇒ p=0.15), due to the limited number of events in this series. Discussion e-Mipi is a new first prognostic index derived from hierarchical clustering. Our results indicate that this approach might allow to model engineered prognostic indexes based on comprehensive analysis of large datasets. Even if promising, it needs validation through its application to independent series of MCL patients. Additional efforts aiming at integrating biological variables in the model are ongoing. Disclosures Gaidano: Amgen: Consultancy, Honoraria; Morphosys: Honoraria; Janssen: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Roche: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria. Ladetto:Celgene: Honoraria; Sandoz: Honoraria; Jannsen: Honoraria; Roche: Honoraria; Abbvie: Honoraria; Acerta: Honoraria.

Prognostic Factors in Patients With Metastatic Germ Cell Tumors Who Experienced Treatment Failure With Cisplatin-Based First-Line Chemotherapy

2010 ◽  
Vol 28 (33) ◽  
pp. 4906-4911 ◽  
Author(s):  
Keyword(s):  
Treatment Failure ◽  
Prognostic Model ◽  
Survival Rates ◽  
Germ Cell Tumors ◽  
Progression Free Survival ◽  
Training Set ◽  
First Line ◽  
Free Survival ◽  
Validation Set ◽  
Line Chemotherapy

Purpose To develop a prognostic model in patients with germ cell tumors (GCT) who experience treatment failure with cisplatin-based first-line chemotherapy. Patients and Methods Data from 1,984 patients with GCT who progressed after at least three cisplatin-based cycles and were treated with cisplatin-based conventional-dose or carboplatin-based high-dose salvage chemotherapy was retrospectively collected from 38 centers/groups worldwide. One thousand five hundred ninety-four (80%) of 1,984 eligible patients were randomly divided into a training set of 1,067 patients (67%) and a validation set of 527 patients (33%). Seminomas were set aside for posthoc analyses. Primary end point was the 2-year progression-free survival after salvage treatment. Results Overall, 990 patients (62%) relapsed and 604 patients (38%) remained relapse free. Histology, primary tumor location, response, and progression-free interval after first-line treatment, as well as levels of alpha fetoprotein, human chorionic gonadotrophin, and the presence of liver, bone, or brain metastases at salvage were identified as independent prognostic variables and used to build a prognostic model in the training set. Survival rates in the training and validation set were very similar. The estimated 2-year progression-free survival rates in patients not included in the training set was 75% in very low risk, 51% in low risk, 40% in intermediate risk, 26% in high risk, and only 6% in very high-risk patients. Due to missing values in individual variables, 69 patients could not reliably be classified into one of these categories. Conclusion Prognostic variables are important in patients with GCT who experienced treatment failure with cisplatin-based first-line chemotherapy and can be used to construct a prognostic model to guide salvage strategies.

scholarly journals Use of serum biomarkers in staging of canine hepatic fibrosis

2019 ◽  
Vol 31 (5) ◽  
pp. 665-673 ◽  
Author(s):  
Maud Menard ◽  
Alexis Lecoindre ◽  
Jean-Luc Cadoré ◽  
Michèle Chevallier ◽  
Aurélie Pagnon ◽  
...  
Keyword(s):  
Liver Biopsy ◽  
Hepatic Fibrosis ◽  
External Validation ◽  
Model Performance ◽  
Area Under The Curve ◽  
Gamma Glutamyl Transferase ◽  
Training Set ◽  
Internal Validation ◽  
Validation Set ◽  
Glutamyl Transferase

Accurate staging of hepatic fibrosis (HF) is important for treatment and prognosis of canine chronic hepatitis. HF scores are used in human medicine to indirectly stage and monitor HF, decreasing the need for liver biopsy. We developed a canine HF score to screen for moderate or greater HF. We included 96 dogs in our study, including 5 healthy dogs. A liver biopsy for histologic examination and a biochemistry profile were performed on all dogs. The dogs were randomly split into a training set of 58 dogs and a validation set of 38 dogs. A HF score that included alanine aminotransferase, alkaline phosphatase, total bilirubin, potassium, and gamma-glutamyl transferase was developed in the training set. Model performance was confirmed using the internal validation set, and was similar to the performance in the training set. The overall sensitivity and specificity for the study group were 80% and 70% respectively, with an area under the curve of 0.80 (0.71–0.90). This HF score could be used for indirect diagnosis of canine HF when biochemistry panels are performed on the Konelab 30i (Thermo Scientific), using reagents as in our study. External validation is required to determine if the score is sufficiently robust to utilize biochemical results measured in other laboratories with different instruments and methodologies.

Efficacy Comparison of Oral Versus Intravenous Busulfan in a BuCy Conditioning Regimen for Allogeneic BMT.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 5042-5042
Author(s):  
Je-Hwan Lee ◽  
Seong-Jun Choi ◽  
Jung-Hee Lee ◽  
Miee Seol ◽  
Young-Shin Lee ◽  
...  
Keyword(s):  
Retrospective Study ◽  
Cumulative Incidence ◽  
Medical Center ◽  
Conditioning Regimen ◽  
P Value ◽  
Allogeneic Bmt ◽  
Transfusion Requirements ◽  
Study Results ◽  
Asan Medical ◽  
Conditioning Therapy

Abstract Intravenous administration of busulfan (I-Bu) or targeted busulfan dosing has replaced oral administration of busulfan (O-Bu) in a conditioning therapy for BMT mainly due to erratic gastrointestinal absorption of oral busulfan. Several retrospective study results have demonstrated that use of I-Bu resulted in lower transplant-related morbidity and mortality compared to O-Bu, but the efficacy of I-Bu and O-Bu has not been compared. In this retrospective study, we compared the efficacy of I-Bu vs. O-Bu in a BuCy conditioning regimen for allogeneic BMT in a single institute. To avoid the bias of retrospective comparison, we restricted the patient eligibility to the followings: patients with AML having intermediate or poor cytogenetic risk groups at the time of diagnosis, those in the first complete remission at the time of BMT, those who were treated with BuCy conditioning regimen, and those who received bone marrow as a stem cell source. A total of 80 patients were eligible in this study among the patients who were transplanted at the Asan Medical Center between December 1993 and July 2007: 42 patients received O-Bu (4 mg/kg/d x 4d) and 38 patients received I-Bu (Busulfex, 3.2 mg/kg/d x 4d). The same dose of cyclophosphamide (60 mg/kg/d x 2d) was given to all the patients. We collected clinical and laboratory data from the BMT database of the Asan Medical Center. The efficacy was compared in terms of cumulative incidence of relapse (CIR), event-free survival (EFS), and overall survival (OS). Propensity score analysis was used to adjust the confounding factors between O-Bu and I-Bu groups. Several baseline clinico-laboratory factors at the time of BMT such as age, number of consolidation therapy prior to BMT, time from diagnosis to BMT, use of methotrexate for GVHD prophylaxis, and transfusion requirement before BMT were significantly different between 2 groups. Times to engraftment, transfusion requirements, infectious complications, hepatic VOD, and acute and chronic GVHD were similar between 2 groups. The cumulative incidence of non-relapse mortality was 14.3% in O-Bu group and 10.3% in I-Bu group (adjusted P-value, 0.990). The CIR at 4-year was 28.6% in O-Bu group and 16.9% in I-Bu group (adjusted P-value, 0.430). The 4-year probabilities of EFS and OS were 57.1% and 64.3% in O-Bu group and 72.6% and 69.3% in I-Bu group (adjusted P-values, 0.496 and 0.634, respectively). In summary, EFS and CIR were superior in I-Bu group compared to O-Bu group without statistical significance. Our results suggest that intravenous busulfan is as effective as oral busulfan in a conditioning therapy for BMT.

MicroRNA Signature Obtained From the Comparison of Aggressive With Indolent Non-Hodgkin Lymphomas: Potential Prognostic Value in Mantle-Cell Lymphoma

2013 ◽  
Vol 31 (23) ◽  
pp. 2903-2911 ◽  
Author(s):  
Rashmi S. Goswami ◽  
Eshetu G. Atenafu ◽  
Yali Xuan ◽  
Levi Waldron ◽  
Patricia P. Reis ◽  
...  
Keyword(s):  
Overall Survival ◽  
Mantle Cell Lymphoma ◽  
Prognostic Model ◽  
Cell Lymphoma ◽  
International Prognostic Index ◽  
Prognostic Index ◽  
Differentially Expressed ◽  
Training Set ◽  
Ki 67 ◽  
Mantle Cell

Purpose Mantle-cell lymphoma (MCL) has a variable natural history but is incurable with current therapies. MicroRNAs (miRs) are useful in prognostic assessment of cancer. We determined an miR signature defining aggressiveness in B-cell non-Hodgkin lymphomas (NHL) and assessed whether this signature aids in MCL prognosis. Methods We assessed miR expression in a training set of 43 NHL cases. The miR signature was validated in 44 additional cases and examined on a training set of 119 MCL cases from four institutions in Canada. miRs significantly associated with overall survival were examined in an independent cohort of 114 MCL cases to determine association with patient outcome. miR expression was combined with current clinical prognostic factors to develop an enhanced prognostic model in patients with MCL. Results Fourteen miRs were differentially expressed between aggressive and indolent NHL; 11 of 14 were validated in an independent set of NHL (excluding MCL). miR-127-3p and miR-615-3p were significantly associated with overall survival in the MCL training set. Their expression was validated in an independent MCL patient set. In comparison with Ki-67, expression of these miRs was more significantly associated with overall survival among patients with MCL. miR-127-3p was combined with Ki-67 to create a new prognostic model for MCL. A similar model was created with miR-615-3p and Mantle Cell Lymphoma International Prognostic Index scores. Conclusion Eleven miRs are differentially expressed between aggressive and indolent NHL. Two novel miRs were associated with overall survival in MCL and were combined with clinical prognostic models to generate novel prognostic data for patients with MCL.

Endoscopic third ventriculostomy in the treatment of childhood hydrocephalus in Uganda: report of a scoring system that predicts success

2010 ◽  
Vol 5 (2) ◽  
pp. 143-148 ◽  
Author(s):  
Benjamin C. Warf ◽  
John Mugamba ◽  
Abhaya V. Kulkarni
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Endoscopic Third Ventriculostomy ◽  
Successful Outcome ◽  
Third Ventriculostomy ◽  
P Value ◽  
Training Set ◽  
Childhood Hydrocephalus ◽  
Validation Set

Object In Uganda, childhood hydrocephalus is common and difficult to treat. In some children, endoscopic third ventriculostomy (ETV) can be successful and avoid dependence on a shunt. This can be especially beneficial in Uganda, because of the high risk of infection and long-term failure associated with shunting. Therefore, the authors developed and validated a model to predict the chances of ETV success, taking into account the unique characteristics of a large sub-Saharan African population. Methods All children presenting with hydrocephalus at CURE Children's Hospital of Uganda (CCHU) between 2001 and 2007 were offered ETV as first-line treatment and were prospectively followed up. A multivariable logistic regression model was built using ETV success at 6 months as the outcome. The model was derived on 70% of the sample (training set) and validated on the remaining 30% (validation set). Results Endoscopic third ventriculostomy was attempted in 1406 patients. Of these, 427 were lost to follow-up prior to 6 months. In the remaining 979 patients, the ETV was aborted in 281 due to poor anatomy/visibility and in 310 the ETV failed during the first 6 months. Therefore, a total of 388 of 979 (39.6% and [55.6% of completed ETVs]) procedures were successful at 6 months. The mean age at ETV was 12.6 months, and 57.8% of cases were postinfectious in origin. The authors' logistic regression model contained the following significant variables: patient age at ETV, cause of hydrocephalus, and whether choroid plexus cauterization was performed. In the training set (676 patients) and validation set (303 patients), the model was able to accurately predict the probability of successful ETV (Hosmer-Lemeshow p value > 0.60 and C statistic > 0.70). The authors developed the simplified CCHU ETV Success Score that can be used in the field to predict the probability of ETV success. Conclusions The authors' model will allow clinicians to accurately identify children with a good chance of successful outcome with ETV, taking into account the unique characteristics and circumstances of the Ugandan population.

scholarly journals The Construction of a Prognostic Model Based on a Peptidyl Prolyl Cis–Trans Isomerase Gene Signature in Hepatocellular Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Huadi Shi ◽  
Fulan Zhong ◽  
Xiaoqiong Yi ◽  
Zhenyi Shi ◽  
Feiyan Ou ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Risk Score ◽  
Prognostic Value ◽  
Prognostic Model ◽  
Stepwise Regression ◽  
Gene Signature ◽  
Training Set ◽  
Model Based ◽  
Kaplan Meier ◽  
Validation Set

Objective: The aim of the present study was to construct a prognostic model based on the peptidyl prolyl cis–trans isomerase gene signature and explore the prognostic value of this model in patients with hepatocellular carcinoma.Methods: The transcriptome and clinical data of hepatocellular carcinoma patients were downloaded from The Cancer Genome Atlas and the International Cancer Genome Consortium database as the training set and validation set, respectively. Peptidyl prolyl cis–trans isomerase gene sets were obtained from the Molecular Signatures Database. The differential expression of peptidyl prolyl cis–trans isomerase genes was analyzed by R software. A prognostic model based on the peptidyl prolyl cis–trans isomerase signature was established by Cox, Lasso, and stepwise regression methods. Kaplan–Meier survival analysis was used to evaluate the prognostic value of the model and validate it with an independent external data. Finally, nomogram and calibration curves were developed in combination with clinical staging and risk score.Results: Differential gene expression analysis of hepatocellular carcinoma and adjacent tissues showed that there were 16 upregulated genes. A prognostic model of hepatocellular carcinoma was constructed based on three gene signatures by Cox, Lasso, and stepwise regression analysis. The Kaplan–Meier curve showed that hepatocellular carcinoma patients in high-risk score group had a worse prognosis (p &lt; 0.05). The receiver operating characteristic curve revealed that the area under curve values of predicting the survival rate at 1, 2, 3, 4, and 5 years were 0.725, 0.680, 0.644, 0.630, and 0.639, respectively. In addition, the evaluation results of the model by the validation set were basically consistent with those of the training set. A nomogram incorporating clinical stage and risk score was established, and the calibration curve matched well with the diagonal.Conclusion: A prognostic model based on 3 peptidyl prolyl cis–trans isomerase gene signatures is expected to provide reference for prognostic risk stratification in patients with hepatocellular carcinoma.

scholarly journals A Coagulation-Related Gene-Based Prognostic Model for Invasive Ductal Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Jing Li ◽  
Jiajia Du ◽  
Yanhong Wang ◽  
Hongyan Jia
Keyword(s):  
Breast Cancer ◽  
Invasive Ductal Carcinoma ◽  
Prognostic Model ◽  
Ductal Carcinoma ◽  
Risk Group ◽  
Metastatic Breast ◽  
Related Gene ◽  
Training Set ◽  
Gene Set ◽  
Validation Set

Background: Invasive ductal carcinoma (IDC) is the most common type of metastatic breast cancer. Due to the lack of valuable molecular biomarkers, the diagnosis and prognosis of IDC remain a challenge. A large number of studies have confirmed that coagulation is positively correlated with angiogenesis-related factors in metastatic breast cancer. Therefore, the purpose of this study was to construct a COAGULATION-related genes signature for IDC using the bioinformatics approaches.Methods: The 50 hallmark gene sets were obtained from the molecular signature database (MsigDB) to conduct Gene Set Variation Analysis (GSVA). Gene Set Enrichment Analysis (GSEA) was applied to analyze the enrichment of HALLMARK_COAGULATION. The COAGULATION-related genes were extracted from the gene set. Then, Limma Package was used to identify the differentially expressed COAGULATION-related genes (DECGs) between ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) samples in GSE26340 data set. A total of 740 IDC samples from The Cancer Genome Atlas (TCGA) database were divided into a training set and a validation set (7:3). The univariate and multivariate Cox regression analyses were performed to construct a risk signature, which divided the IDC samples into the high- and low-risk groups. The overall survival (OS) curve and receiver operating characteristic (ROC) curve were drawn in both training set and validation set. Finally, a nomogram was constructed to predict the 1-, 2-, 3-, 4-, and 5-year survival rates of IDC patients. Quantitative real-time fluorescence PCR (qRT-PCR) was performed to verify the expression levels of the prognostic genes.Results: The “HALLMARK_COAGULATION” was significantly activated in IDC. There was a significant difference in the clinicopathological parameters between the DCIS and IDC patients. Twenty-four DECGs were identified, of which five genes (SERPINA1, CAPN2, HMGCS2, MMP7, and PLAT) were screened to construct the prognostic model. The high-risk group showed a significantly lower survival rate than the low-risk group both in the training set and validation set (p=3.5943e-06 and p=0.014243). The risk score was demonstrated to be an independent predictor of IDC prognosis. A nomogram including risk score, pathological_stage, and pathological_N provided a quantitative method to predict the survival probability of 1-, 2-, 3-, 4-, and 5-year in IDC patients. The results of decision curve analysis (DCA) further demonstrated that the nomogram had a high potential for clinical utility.Conclusion: This study established a COAGULATION-related gene signature and showed its prognostic value in IDC through a comprehensive bioinformatics analysis, which may provide a potential new prognostic mean for patients with IDC.

scholarly journals Deconvolution of Bulk Gene Expression Profiles with Single-Cell Transcriptomics to Develop a Cell Type Composition-Based Prognostic Model for Acute Myeloid Leukemia

2021 ◽  
Vol 9 ◽  
Author(s):  
Chengguqiu Dai ◽  
Mengya Chen ◽  
Chaolong Wang ◽  
Xingjie Hao
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Single Cell ◽  
Myeloid Leukemia ◽  
Prognostic Model ◽  
Prognostic Score ◽  
Cell Type ◽  
Training Set ◽  
Validation Set ◽  
Acute Myeloid

Acute myeloid leukemia (AML) is one of the malignant hematologic cancers with rapid progress and poor prognosis. Most AML prognostic stratifications focused on genetic abnormalities. However, none of them was established based on the cell type compositions (CTCs) of peripheral blood or bone marrow aspirates from patients at diagnosis. Here we sought to develop a novel prognostic model for AML in adults based on the CTCs. First, we applied the CIBERSORT algorithm to estimate the CTCs for patients from two public datasets (GSE6891 and TCGA-LAML) using a custom gene expression signature reference constructed by an AML single-cell RNA sequencing dataset (GSE116256). Then, a CTC-based prognostic model was established using least absolute shrinkage and selection operator Cox regression, termed CTC score. The constructed prognostic model CTC score comprised 3 cell types, GMP-like, HSC-like, and T. Compared with the low-CTC-score group, the high-CTC-score group showed a 1.57-fold [95% confidence interval (CI), 1.23 to 2.00; p = 0.0002] and a 2.32-fold (95% CI, 1.53 to 3.51; p &lt; 0.0001) higher overall mortality risk in the training set (GSE6891) and validation set (TCGA-LAML), respectively. When adjusting for age at diagnosis, cytogenetic risk, and karyotype, the CTC score remained statistically significant in both the training set [hazard ratio (HR) = 2.25; 95% CI, 1.20 to 4.24; p = 0.0119] and the validation set (HR = 7.97; 95% CI, 2.95 to 21.56; p &lt; 0.0001]. We further compared the performance of the CTC score with two gene expression-based prognostic scores: the 17-gene leukemic stem cell score (LSC17 score) and the AML prognostic score (APS). It turned out that the CTC score achieved comparable performance at 1-, 2-, 3-, and 5-years timepoints and provided independent and additional prognostic information different from the LSC17 score and APS. In conclusion, the CTC score could serve as a powerful prognostic marker for AML and has great potential to assist clinicians to formulate individualized treatment plans.

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