scholarly journals PPARG, GNG12, and CD19 are Potential Independent Predictors of Central Nerve Recurrence in Childhood Acute Lymphoblastic Leukemia

2021 ◽  
Author(s):  
Shan Zhang ◽  
Yansong Tu ◽  
Qianmiao Wu ◽  
Huijun Chen ◽  
Huaijun Tu ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Acute Lymphoblastic Leukemia ◽  
Phase I ◽  
Cox Regression ◽  
Lymphoblastic Leukemia ◽  
Validation Group ◽  
Hub Genes ◽  
Cox Regression Analysis ◽  
Cox Analysis ◽  
Target Database

Abstract Objective: To identify biomarkers that can predict the recurrence of the central nervous system (CNS) in children with acute lymphoblastic leukemia (ALL), and establish a prediction model. Materials and Methods: The transcriptome and clinical data collected by the Children's Oncology Group (COG) collaboration group in the Phase II study (use for test group) and Phase I study (use for validation group) of ALL in children were downloaded from the TARGET database. Transcriptome data were analyzed by bioinformatics method to identify core (hub) genes and establish a risk assessment model. Univariate Cox analysis was performed on each clinical data, and multivariate Cox regression analysis was performed on the obtained results and risk score. The children ALL phase I samples collected by the COG collaboration group in the TARGET database were used for verification. Results: A total of 1230 differentially expressed genes were screened out between the CNS relapsed and non-relapsed groups. Univariate multivariate Cox analysis of 10 hub genes identified showed that PPARG (HR=0.78, 95%CI=0.67-0.91, p=0.007), CD19 (HR=1.15, 95%CI=1.05-1.26, p=0.003) and GNG12 (HR=1.25, 95%CI=1.04-1.51, p=0.017) had statistical differences. The risk score was statistically significant in univariate (HR=3.06, 95%CI=1.30-7.19, p=0.011) and multivariate (HR=1.81, 95%CI=1.16-2.32, p=0.046) Cox regression analysis. The survival analysis results of the high and low-risk groups were different when the validation group was substituted into the model (p=0.018). In addition, the CNS involvement grading status at first diagnosis CNS3 vs. CNS1 (HR=5.74, 95%CI=2.01-16.4, p=0.001), T cell vs B cell (HR=1.63, 95% CI=1.06-2.49, p=0.026) were also statistically significant. Conclusions: PPARG, GNG12, and CD19 may be predictors of CNS relapse in childhood ALL.

Prognostic Factors in CD10 Negative Precursor B-Cell Acute Lymphoblastic Leukemia in Children: Data from Three Consecutive Trials ALL-BFM 86, 90, and 95.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 1957-1957
Author(s):  
Anja Möricke ◽  
Richard Ratei ◽  
Wolf-Dieter Ludwig ◽  
Jochen Harbott ◽  
Arndt Borkhardt ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Prognostic Factors ◽  
Acute Lymphoblastic Leukemia ◽  
B Cell ◽  
Cox Regression ◽  
Lymphoblastic Leukemia ◽  
Cns Involvement ◽  
Total N ◽  
Cox Regression Analysis ◽  
Cell Acute Lymphoblastic Leukemia

Abstract The overall unfavorable prognosis of CD10 negative (CD10−) precursor B-cell acute lymphoblastic leukemia (BCP-ALL) is well known. We analyzed 4473 pediatric patients (pts) <18 years (y) with BCP-ALL and immunophenotyping of CD10 enrolled from 1986 to 2000 in three consecutive ALL-BFM trials to explore prognostic factors in the CD10− subset. CD10 negativity was defined by CD10 expression in <20% of blasts. 233 pts (5.2%) were CD10−. In comparison to CD10 positive (CD10+) BCP-ALL pts, CD10− pts comprised more infants (age <1y 34% vs. 1%, p(X2)<0.001), more cases with hyperleukocytosis (WBC ≥100/nl 43% vs. 6%, p<0.001), more CNS involvement (CNS positive 10% vs. 2%; p<0.001) and an impaired treatment response (prednisone poor response (PPR) 22% vs. 5%, p<0.001; induction failure 6% vs. 1%, p<0.001). Estimated probability of 5 years event free survival (5y-pEFS) was significantly lower in pts with CD10− as compared to CD10+ BCP-ALL (49±3% vs 81±0.6%, p(log-rank)<0.001). Cox regression analysis including age, WBC, prednisone response (PR) and MLL/AF4 status as covariables revealed CD10 negativity as independent prognostic factor (RR 1.5, 95% confidence interval (CI) 1.1–2.1, p=0.01). Further analyses were performed within the CD10− group: 83% of infants and 60% of pts ≥1y were successfully analyzed for MLL/AF4. MLL/AF4 was detected in 55% of pts <1y and 27% of pts ≥1y. The well known risk factors for BCP-ALL (sex, age, WBC, CNS involvement, MLL/AF4 and PPR) also had prognostic impact within the CD10− group: n* 5y-pEFS* (%) SE (%) p (log-rank) *5 pts w/o reinduction were excluded sex female 109 55 5 0.022 male 119 40 5 age <1y 78 25 5 <0.001 ≥1y 150 62 4 WBC <100/nl 128 62 4 <0.001 ≥100/nl 100 33 5 CNS neg 181 54 4 0.011 pos 21 33 10 MLL/AF4 neg 95 53 5 0.001 pos 61 29 6 PR good 170 57 4 <0.001 poor 50 30 6 Out of a number of immunophenotypic markers, analyzed at different expression cut-off points, CD24 at missing or weak expression of <40% and CD65 at high expression of ≥40% were significantly correlated with unfavorable clinical characteristics and worse outcome within the CD10− group. Significant correlation with PR could only be demonstrated for expression of CD24, which is presumed to act as negative regulator in B-cell development through mediation of apoptosis. age<1y* WBC ≥100/nl* MLL/AF4 pos* PPR# pEFS§ n/total (%) n/total (%) n/total (%) n/total (%) % ±SE * all p(X2)<0.01, #CD24 p=0.01, CD65 n.s., §all p(log-rank]<0.001 CD24 <40% 37/77 (48) 52/77 (68) 33/56 (59) 24/73 (33) 32 ±5 CD24 ≥40% 34/122 (28) 35/122 (29) 18/76 (24) 20/119 (17) 59 ±5 CD65 <40% 56/180 (31) 67/180 (37) 39/120 (33) 39/175 (22) 30 ±7 CD65 ≥40% 22/44 (50) 32/44 (73) 21/34 (62) 10/41 (24) 54 ±4 Including age, WBC, PR and MLL/AF4 status as covariables, out of the analyzed markers only CD65 proved to be an independent prognostic factor in CD10− BCP-ALL (Cox regression analysis: RR 1.5, 95% CI 1.1–2.9, p=0.018). The identification of additional prognosis associated immunophenotypic markers may contribute to further refinement of treatment strategies for CD10− BCP-ALL pts.

NIH-Defined Graft-Versus-Host Disease in Patients with Acute Lymphoblastic Leukemia: Natural History, Prognostic Impact and Effect of Donor Lymphocyte Infusions

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 4547-4547
Author(s):  
Theis H. Terwey ◽  
Tanja M. Le Duc ◽  
Philipp G. Hemmati ◽  
Lam G. Vuong ◽  
Peter Martus ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Acute Lymphoblastic Leukemia ◽  
Cumulative Incidence ◽  
Cox Regression ◽  
Lymphoblastic Leukemia ◽  
Prognostic Impact ◽  
Cox Regression Analysis ◽  
Graft Versus Host ◽  
Grade Iii ◽  
Donor Lymphocyte Infusions

Abstract Abstract 4547 Introduction: The 2005 NIH consensus criteria (NCC) for acute and chronic graft-versus-host disease (aGVHD, cGVHD) are the gold standard for classifying GVHD in trials but they are not routinely used in the clinic, in part due to uncertainty about their prognostic value. To address this limitation we analyzed NIH-defined GVHD in 147 consecutive acute lymphoblastic leukemia (ALL) patients who received a first myeloablative transplant at our center between 1995 and 2009. Methods: Median age was 31 years (range: 17–56). Disease status was CR1 (50%), CR>1 (22%) or no CR (28%). Myeloablative conditioning consisted of 12 Gy TBI ± etoposide ± cyclophosphamide. Donors were HLA-matched related (42%), -matched unrelated (46%) or -mismatched (12%) and peripheral blood stem cells (74%) or bone marrow (26%) were given. GVHD-prophylaxis consisted of CSA/MTX (72%), CSA/prednisolone (19%) or other CSA-based regimens (9%). ATG was given in HLA-mismatched transplants (12%) and since 2005 also in matched unrelated transplants (11%), according to GMALL study protocols. Preemptive donor lymphocyte infusions (DLI) were a treatment option in case of mixed chimerism or minimal residual disease. Results: Median follow-up was 60 months (8–185). Projected overall survival (OS) at 1, 2 and 5 years was 64%, 56% and 49%. 5-year cumulative incidence of relapse was 33% and of non-relapse mortality (NRM) 25% (7% infections, 9% aGVHD, 7% cGVHD, 2% other). Median time until onset of classic aGVHD was 20 days (5–95). Cumulative incidence of classic aGVHD was 41% for grade I/II and 29% for grade III/IV. Among patients with classic aGVHD, skin, liver or gut involvement was seen in 94%, 32% and 34%. Late aGVHD was observed in 12% at a median of 100 days (range 100–240). Among late aGVHD cases 82% were subclassified as persistent or recurrent classic aGVHD. Median time until onset of chronic GVHD was 115 days (14–294) measured from transplant or DLI with a cumulative incidence for mild, moderate and severe forms of 13%, 15% and 25%. Mouth, skin, eyes, liver, joints and fascia, gut, lung and other organs were involved in 91%, 70%, 61%, 48%, 27%, 19%, 10% and 6% of cGVHD cases. cGVHD was subclassified as classic cGVHD and overlap syndrome in 40% and 60% of cases. 62% had progressive or quiescent type of onset. In multivariate Cox regression analysis with GVHD as time-dependant covariate (table 1) classic aGVHD grade III/IV was associated with inferior OS due to higher NRM. Comparable effects were seen for late aGVHD. In contrast, moderate and severe cGVHD were associated with superior OS due to lower relapse incidence. Classic and overlap cGVHD had no differential prognostic impact. 34 patients without GVHD after cessation of immunosuppression received preemptive DLI. In this subgroup cumulative incidence of classic aGVHD, late aGVHD or cGVHD was 62%, 6% and 62%. Organ involvement was comparable to non-DLI associated GVHD. In a time-dependant multivariate analysis, patients who developed NIH-defined cGVHD after DLI had improved OS (HR 0.21, 95%CI: 0.054–0.81, P=0.023) due to lower relapse incidence (HR 0.26, 95%CI: 0.043–0.91, P=0.048) compared to patients without cGVHD after DLI. Conclusions: This is the first study on the natural history and prognostic impact of NIH-defined GVHD in ALL patients. We found that severe classic aGVHD leads to higher NRM and inferior OS with similar effects seen for late aGVHD. cGVHD had a positive impact on OS and relapse rate, both after transplant and after preemptive DLI, indicating a potent graft-versus-leukemia effect. Although our cohort contains some heterogeneity we believe that this data supports the use of the NCC as diagnostic and prognostic tool in ALL patients. Multivariate Cox regression analysis for OS, relapse and NRM with GVHD as time-dependant covariate. Only results for GVHD are shown. Disclosures: No relevant conflicts of interest to declare.

Effects Of Metformin Addition To a Standard Chemotherapy Regimen For The Treatment Of Adult Acute Lymphoblastic Leukemia. An In Vitro and In Vivo study

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 5024-5024
Author(s):  
Christian Omar Ramos Peñafiel ◽  
Irma Olarte Carrillo ◽  
Jorge Zamora Domínguez ◽  
Humberto Baldemar Castellanos Sinco ◽  
Etta Rozen Fuller ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Acute Lymphoblastic Leukemia ◽  
Odds Ratio ◽  
Cox Regression ◽  
Lymphoblastic Leukemia ◽  
Control Group ◽  
Cox Regression Analysis ◽  
Adult Acute Lymphoblastic Leukemia

Abstract Antitumor effects of metformin are widely known. Unfortunately their use in the treatment of acute lymphoblastic leukemia is limited. Study design The study consisted of two stages Phase 1: Cell assay adding metformin (40mM) assessing the viability and cell cycle in the cell line molt 4 Phase 2: Pilot study adding Metformin (850mg three time day) during the pre-treatment with steroids and the induction remission phase versus a control group (2:1 randomization) Statistical analysis Chi-square analysis was used to corroborate the hypothesis. The odds ratio was calculated for both, the absence of Good steroid response and refractory leukemia. Cox regression analysis and Kaplan-Meier curves were used for the survival analysis Results Celular assay. Metformin inhibited cell viability at 120hours reducing the percentage of cells in phase S. Clinical assay. 151 patients were studied, 44 (29.1%) on Metformin arm, of these 59.1% ( n=26) archived a GSR compared with the control group (26.2%, n=28). A greater number of complete remission were presented in Metformin arm (81.8% versus 57.9%) shown to be a protective factor for GSR and complete remissions (odds ratio ; 0.2454 y 0.3062 respectively). In the Cox regression analysis, Metformin significantly impact in the global survival (p=0,012,95% IC) versus the other variables studied. Conclusions Metformin is useful both in vivo and in vitro treatment of adult acute lymphoblastic leukemia. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Identification and Analysis of Three Hub Prognostic Genes Related to Osteosarcoma Metastasis

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Jianye Tan ◽  
Haofeng Liang ◽  
Bingsheng Yang ◽  
Shuang Zhu ◽  
Guofeng Wu ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Cox Regression ◽  
Survival Rates ◽  
Prognostic Biomarkers ◽  
Messenger Rnas ◽  
Hub Genes ◽  
Cox Regression Analysis ◽  
Expression Levels ◽  
Kaplan Meier ◽  
Before And After

Osteosarcoma (OS) often occurs in children and often undergoes metastasis, resulting in lower survival rates. Information on the complexity and pathogenic mechanism of OS is limited, and thus, the development of treatments involving alternative molecular and genetic targets is hampered. We categorized transcriptome data into metastasis and nonmetastasis groups, and 400 differential RNAs (230 messenger RNAs (mRNAs) and 170 long noncoding RNAs (lncRNAs)) were obtained by the edgeR package. Prognostic genes were identified by performing univariate Cox regression analysis and the Kaplan–Meier (KM) survival analysis. We then examined the correlation between the expression level of prognostic lncRNAs and mRNAs. Furthermore, microRNAs (miRNAs) corresponding to the coexpression of lncRNA-mRNA was predicted, which was used to construct a competitive endogenous RNA (ceRNA) regulatory network. Finally, multivariate Cox proportional risk regression analysis was used to identify hub prognostic genes. Three hub prognostic genes (ABCG8, LOXL4, and PDE1B) were identified as potential prognostic biomarkers and therapeutic targets for OS. Furthermore, transcriptions factors (TFs) (DBP, ESX1, FOS, FOXI1, MEF2C, NFE2, and OTX2) and lncRNAs (RP11-357H14.16, RP11-284N8.3, and RP11-629G13.1) that were able to affect the expression levels of genes before and after transcription were found to regulate the prognostic hub genes. In addition, we identified drugs related to the prognostic hub genes, which may have potential clinical applications. Immunohistochemistry (IHC) and quantitative real-time polymerase chain reaction (qRT-PCR) confirmed that the expression levels of ABCG8, LOXL4, and PDE1B coincided with the results of bioinformatics analysis. Moreover, the relationship between the hub prognostic gene expression and patient prognosis was also validated. Our study elucidated the roles of three novel prognostic biomarkers in the pathogenesis of OS as well as presenting a potential clinical treatment for OS.

scholarly journals Prognostic model of head and neck squamous cell carcinoma based on 12 ferroptosis-related genes

2021 ◽  
Author(s):  
Sijia Li ◽  
Hongyang Zhang ◽  
Wei Li
Keyword(s):  
Regression Analysis ◽  
Risk Score ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Risk Scores ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Model Based ◽  
Cox Analysis

Abstract Background: The purpose of our study is establishing a model based on ferroptosis-related genes predicting the prognosis of patients with head and neck squamous cell carcinoma (HNSCC).Methods: In our study, transcriptome and clinical data of HNSCC patients were from The Cancer Genome Atlas, ferroptosis-related genes and pathways were from Ferroptosis Signatures Database. Differentially expressed genes (DEGs) were screened by comparing tumor and adjacent normal tissues. Functional enrichment analysis of DEGs, protein-protein interaction network and gene mutation examination were applied. Univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression were used to identified DEGs. The model was constructed by multivariate Cox regression analysis and verified by Kaplan-Meier analysis. The relationship between risk scores and other clinical features was also analyzed. Univariate and multivariate Cox analysis was used to verified the independence of our model. The model was evaluated by receiver operating characteristic analysis and calculation of the area under the curve (AUC). A nomogram model based on risk score, age, gender and TNM stages was constructed.Results: We analyzed data including 500 tumor tissues and 44 adjacent normal tissues and 259 ferroptosis-related genes, then obtained 73 DEGs. Univariate Cox regression analysis screened out 16 genes related to overall survival, and LASSO analysis fingered out 12 of them with prognostic value. A risk score model based on these 12 genes was constructed by multivariate Cox regression analysis. According to the median risk score, patients were divided into high-risk group and low-risk group. The survival rate of high-risk group was significantly lower than that of low-risk group in Kaplan-Meier curve. Risk scores were related to T and grade. Univariate and multivariate Cox analysis showed our model was an independent prognostic factor. The AUC was 0.669. The nomogram showed high accuracy predicting the prognosis of HNSCC patients.Conclusion: Our model based on 12 ferroptosis-related genes performed excellently in predicting the prognosis of HNSCC patients. Ferroptosis-related genes may be promising biomarkers for HNSCC treatment and prognosis.

Intensification of Mercaptopurine/Methotrexate Maintenance Chemotherapy May Increase the Risk of Relapse for Some Children With Acute Lymphoblastic Leukemia

2003 ◽  
Vol 21 (7) ◽  
pp. 1332-1339 ◽  
Author(s):  
Kjeld Schmiegelow ◽  
Olle Björk ◽  
Anders Glomstein ◽  
Göran Gustafsson ◽  
Niels Keiding ◽  
...  
Keyword(s):  
Acute Lymphoblastic Leukemia ◽  
Maintenance Therapy ◽  
Cox Regression ◽  
Lymphoblastic Leukemia ◽  
Tpmt Activity ◽  
Control Group ◽  
Cox Regression Analysis ◽  
Cell Counts ◽  
Increased Risk ◽  
Risk Of Relapse

Purpose: Thioguanine nucleotides (TGNs) mediate the cytotoxicity of mercaptopurine (MP). Methylated MP metabolites (formed by thiopurine methyltransferase [TPMT]) and methotrexate (MTX) polyglutamates can inhibit de novo purine synthesis. We explored whether dose adjustment of MP and MTX by erythrocyte (E) levels of TGN and MTX (including polyglutamates) could improve outcome in childhood acute lymphoblastic leukemia (ALL). Patients and Methods: A total of 538 children with ALL were randomly assigned to have their oral MP/MTX maintenance therapy adjusted by white cell counts (WBC), E-TGN, and E-MTX (pharmacology group), or by WBC only (control group). Results: After a median follow-up of 7.8 years, 79 patients had relapsed. Cox regression analysis showed an increased risk of relapse for boys (P = .00003), high WBC at diagnosis (P = .03), pharmacology arm (6.6 times increased relapse hazard for girls), high TPMT activity (P = .002), and high average neutrophil counts during maintenance therapy (P = .0009), with a significant interaction between sex and randomization group (P = .0007). For girls, the relapse risk was 5% in the control group and 19% in the pharmacology group (P = .001) because of an increased relapse hazard during the first year after cessation of therapy. TPMT activity was the most significant predictor of relapses among girls in the pharmacology arm (P < .0001). Overall, the TPMT activity was higher for patients who relapsed after cessation of therapy compared with those who stayed in remission (girls 19.5 v 17.4 U/mL, P = .03; boys 19.3 v 18.0 U/mL, P = .04). Conclusion: Adding pharmacologically guided treatment intensification to dose adjustments by blood counts may not be warranted for girls, whereas new approaches to optimize maintenance therapy are needed for boys.

scholarly journals Logistic Regression Analysis of the Factors Involved in the Failure of Osseointegration and Survival of Dental Implants with an Internal Connection and Machined Collar: A 6-Year Retrospective Cohort Study

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Aritza Brizuela-Velasco ◽  
Ángel Álvarez-Arenal ◽  
Esteban Pérez-Pevida ◽  
Iker Bellanco-De La Pinta ◽  
Héctor De Llanos-Lanchares ◽  
...  
Keyword(s):  
Risk Factors ◽  
Regression Analysis ◽  
Dental Implants ◽  
Cox Regression ◽  
Rank Test ◽  
Cox Regression Analysis ◽  
Internal Connection ◽  
Study Results ◽  
Logit Function ◽  
Cox Analysis

Background. Although the long-term success rate of dental implants is currently close to 95%, it is necessary to provide more evidence on the factors related to the failure of osseointegration and survival. Purpose. To establish the risk factors associated with the failure of osseointegration and survival of dental implants with an internal connection and machined collar and to establish a predictive statistical model. Materials and Methods. An analytical, retrospective, and observational clinical study of a sample of 297 implants with a follow-up of up to 76 months. Independent variables related to the implant, patient, and surgical and rehabilitative procedures were identified. The dependent variables were failure of osseointegration and failure of implant survival after prosthetic loading. A survival analysis was carried out by applying the Kaplan-Meier model (significance for p < 0.05 ). The log-rank test and the Cox regression analysis were applied to the factors that presented differences. Finally, the regression logit function was used to determine whether it is possible to predict the risk of implant failure according to the analyzed variables with the data obtained in this study. Results. The percentages of osseointegration and survival were 97.6 and 97.2%, respectively. For osseointegration, there were significant differences according to gender ( p = 0.048 ), and the risk of nonosseointegration was 85% lower in women. Regarding survival, the Cox analysis converged on only two factors, which were smoking and treatment with anticoagulant drugs. The risk of loss was multiplied by 18.3 for patients smoking more than 10 cigarettes per day and by 28.2 for patients treated with anticoagulants. Conclusions. The indicated risk factors should be considered, but the analysis of the results is not sufficient to create a predictive model.

scholarly journals Gene Expression Analysis Reveals Novel Gene Prognostic Signatures Involved in Medulloblastoma Subgroups

2021 ◽  
Author(s):  
Fangcheng Li ◽  
Hong-Yao Yuan ◽  
Cheng Chen ◽  
Jun-Ping Pan ◽  
Xin-Ke Xu ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Gene Expression Analysis ◽  
Cox Regression ◽  
Molecular Subtypes ◽  
Molecular Subtype ◽  
Specific Treatment ◽  
Single Factor ◽  
Hub Genes ◽  
Cox Regression Analysis ◽  
Pathway Enrichment

Abstract PurposeMedulloblastoma is a malignant childhood tumor with four molecular subtypes: WNT, SHH, G3, and G4. The prognosis of these four molecular subtypes is different. WNT has the best prognosis, followed by SHH, and G3 and G4 subtypes have the worst prognosis. This study aimed to identify various molecular subtypes of medulloblastoma can independently predict the prognosis of patients and provide specific treatment way for them.MethodsBased on the data in the GSE37418 dataset, the WGCNA method was used to find the genes most related to these molecular subtypes, and then the top ten hub genes in each subtype were found through the cytohubba plug-in of cytoscape. GO pathway enrichment of four interested modules was used, and then GSE85217 was used for clinical trials in single-factor Cox regression analysis .ResultsThe information was subjected to single-factor Cox regression analysis, and twelve hub genes with the most significant prognostic effects on medulloblastoma were found, and then these genes were subjected to multi-factor Cox regression analysis on each molecular subtype, and finally GNG3 was determined .The combination of CALCB and GCGR can predict the development of SHH well (p=0.0011, AUC=0.734), SOCS3 and HOXC10 can better predict the development of G4 (p=0.044, AUC=0.618), and the combination of ADCY8 and LHX3 can predict G3 Development (p=0.034, AUC=0.675).ConclusionThis report showed a possible evidence that OS-related features of various molecular subtypes of medulloblastoma can independently predict the prognosis of patients with each subtype of medulloblastoma, and provide new therapeutic targets for them.

Analysis of prognostic factors in chemo-naïve patients with advanced NSCLC and poor performance status (PS): Cox regression analysis of two phase III trials

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 7113-7113 ◽  
Author(s):  
M. O’Brien ◽  
P. Bonomi ◽  
C. Langer ◽  
K. O’Byrne ◽  
B. Bandstra ◽  
...  
Keyword(s):  
Weight Loss ◽  
Regression Analysis ◽  
Advanced Nsclc ◽  
Cox Regression ◽  
Phase Iii ◽  
Two Phase ◽  
Cox Regression Analysis ◽  
Phase Iii Trials ◽  
Baseline Factors ◽  
Cox Analysis

7113 Background: Two phase III trials in chemo-naïve PS2 patients with advanced NSCLC compared paclitaxel poliglumex (PPX) to either gemcitabine or vinorelbine (STELLAR 4), or PPX/carboplatin to paclitaxel/carboplatin (STELLAR 3). While overall survival (OS) was similar between treatment arms in both studies, individual patient characteristics may be predictive of benefit. Methods: STELLAR 3 and STELLAR 4 enrolled 400 and 381 chemo-naïve PS2 patients, respectively. The impact of pre-defined baseline characteristics on OS was evaluated by univariate and step-wise multivariate Cox regression analysis. Treatment differences between subgroups were also estimated by Cox analysis. Results: Univariate Cox analysis of potential risk factors showed pre-baseline weight loss, extra-thoracic metastasis, and a low lung cancer symptom (LCS) score to be highly significant (p < 0.001). In STELLAR 4, tobacco use was also a highly significant risk factor. Important primary baseline factors predicting survival as determined by multivariate analysis are summarized in the table . Other baseline factors evaluated but not predictive of survival included gender, number of comorbidities, age, and history of tobacco use. Treatment differences between subgroups were not statistically significant; however, a strong trend towards improved survival was observed for women receiving PPX in STELLAR 4 compared to those in the control-arm (HR = 0.65; p = 0.069). In contrast, men had similar survival between treatment arms (HR = 1.08; p = 0.579). Conclusion: In this large PS2 patient population, weight loss, presence of extra-thoracic metastasis, low LCS scores, and high LDH were found to be important clinical determinants of survival. In addition, significant differences in survival based on geographic region in STELLAR 3 highlight the importance of stratification by region. [Table: see text] [Table: see text]

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