Project description:AimsThe ability of a patient to receive anti-cancer treatment depends on a variety of factors, including performance status (PS), which is typically measured using the Eastern Cooperative Oncology Group (ECOG) scale. This study hypothesized that there would be a strong and positive correlation between ECOG PS values and healthcare resource utilization (HCRU) and a strong and negative correlation with the use of anti-cancer therapy.Materials and methodsPatients with colorectal, lung or gastric cancer were included in this retrospective analysis of administrative claims data linked to electronic medical records (EMR). All-cause HCRU (hospitalization/inpatient care, emergency room visits, systemic anti-cancer therapy, radiation therapy, outpatient physician visits, hospice, home health care and key supportive care treatments such as anti-emetics, hematopoietic treatments, transfusions, and durable medical equipment) was evaluated by baseline ECOG PS value and PS over time. Adjusted multivariable regression analysis was used to assess the relationship between baseline ECOG PS and HCRU. Regression analyses were conducted to explore the relationship between other baseline variables and HCRU.ResultsThere were 1311 patients included in this study. There was low correlation between PS and any HCRU variable or receipt of anti-cancer therapy (correlation coefficients all <0.10). In regression analyses, the proportion of patients with poor PS (PS = 2+) who were hospitalized was not significantly different from those with good PS (PS = 0/1) (28.9% versus 19.3%, p = .07).LimitationsThe low rate of reporting of PS and the small sample size of patient groups in this study.ConclusionsThere is very little evidence of a relationship between ECOG PS and HCRU, ECOG PS, or anti-cancer therapy in this study, in part due to low rates of and lack of variability in reported PS. There is some evidence that baseline comorbidities were significantly associated with HCRU and should be accounted for in future research evaluating HCRU.

Project description:BackgroundRecent data in esophageal cancer suggests the variant allele of a single-nucleotide polymorphism (SNP) in XRCC1 may be associated with resistance to radiochemotherapy. However, this SNP has not been assessed in a histologically homogeneous clinical trial cohort that has been treated with a uniform approach. In addition, whether germline DNA may serve as a surrogate for tumor genotype at this locus is unknown in this disease. Our objective was to assess this SNP in relation to the pathologic complete response (pCR) rate in subjects with esophageal adenocarcinoma who received cisplatin-based preoperative radiochemotherapy in a multicenter clinical trial (Eastern Cooperative Oncology Group 1201). As a secondary aim, we investigated the rate of allelic imbalance between germline and tumor DNA.MethodsEighty-one eligible treatment-naïve subjects with newly diagnosed resectable esophageal adenocarcinoma received radiotherapy (45 Gy) concurrent with cisplatin-based chemotherapy, with planned subsequent surgical resection. The primary endpoint was pCR, defined as complete absence of tumor in the surgical specimen after radiochemotherapy. Using germline DNA from 60 subjects, we examined the base-excision repair SNP, XRCC1 Arg399Gln, and 4 other SNPs in nucleotide excision (XPD Lys751Gln and Asp312Asn, ERCC1 3' flank) and double-stranded break (XRCC2 5' flank) repair pathways, and correlated genotype with pCR rate. Paired tumor tissue was used to estimate the frequency of allelic imbalance at the XRCC1 SNP.ResultsThe variant allele of the XRCC1 SNP (399Gln) was detected in 52% of subjects. Only 6% of subjects with the variant allele experienced a pCR, compared to 28% of subjects without the variant allele (odds ratio 5.37 for failing to achieve pCR, p = 0.062). Allelic imbalance at this locus was found in only 10% of informative subjects, suggesting that germline genotype may reflect tumor genotype at this locus. No significant association with pCR was noted for other SNPs.ConclusionsAssessed for the first time in a prospective, interventional trial cohort of esophageal adenocarcinoma, XRCC1 399Gln was associated with resistance to radiochemotherapy. Further investigation of this genetic variation is warranted in larger cohorts. In addition, these data indicate that germline genotype may serve as a surrogate for tumor genotype at this locus.

Project description:PAPER 1:"Identification of novel subgroups of high-risk pediatric precursor B acute lymphoblastic leukemia (B-ALL) by unsupervised microarray analysis: clinical correlates and therapeutic implications. A Children's Oncology Group (COG) study." ABSTRACT We examined gene expression profiles of pre-treatment specimens from 207 patients from the COG P9906 study to identify signatures of children with high risk B-precursor acute lymphoblastic leukemia (ALL) and to determine whether the resulting clusters are associated with either specific clinical features or treatment response characteristics. Four unsupervised clustering methods were utilized to classify patients into similar groups. The different clustering algorithms showed significant overlap in cluster membership. Two clusters contained all cases with either t(1;19)(q23;p13) translocations or MLL rearrangements. The other six clusters were novel and had no recurring chromosomal abnormalities or distinctive clinical features. Members of two of these novel clusters had significant survival differences when compared to the overall 4-year relapse-free survival (RFS) of 61%. These included clusters of patients with either significantly better (94.7%) or worse (21.0%) RFS at 4 years. Children of Hispanic/Latino ethnicity were disproportionately present in the poor outcome cluster. The poor outcome cluster represents a novel biologically distinctive subset of B-precursor ALL that may occur at least as frequently as BCR/ABL. Further molecular characterization of this cluster may lead to the discovery of genomic abnormalities that can be targeted to improve the currently dismal outcome for children with this gene signature. The Sample data have also been used in another study: PAPER 2: "Gene expression classifiers for minimal residual disease and relapse free survival improve outcome prediction and risk classification in children with high risk acute lymphoblastic leukemia. A Children's Oncology Group study". ABSTRACT Background. Nearly 25% of children with B-precursor ALL present with "high-risk" disease (HR-ALL) that is resistant to current therapies. Gene expression profiling may yield molecular classifiers for outcome prediction that can be used to improve risk classification and therapeutic targeting. Methods. Expression profiles were obtained in pre-treatment leukemic samples from 207 uniformly treated children with HR-ALL. Relapse free survival (RFS) was 61% at 4 years and flow cytometric measures of minimal residual disease (MRD) at the end of induction (day 29) were predictive of outcome (P<0.001). Molecular classifiers predictive of RFS and MRD were developed using extensive cross-validation procedures. Results. A 38 gene molecular risk classifier predictive of RFS (MRC-RFS) distinguished two groups in HR-ALL with different relapse risks: low (4 yr RFS: 81%, n=109) vs. high (4 yr RFS: 50%, n=98) (P<0.0001). In multivariate analysis, the best predictor combined MRC-RFS and day 29 flow MRD data, classifying children into low (87% RFS), intermediate (62% RFS), or high risk (29% RFS) groups (P<0.0001). A 21 gene molecular classifier predictive of MRD could effectively substitute for day 29 flow MRD, yielding a combined classifier that similarly distinguished three risk groups at pre-treatment (low: 82% RFS; intermediate: 63% RFS; and high risk: 45% RFS) (P<0.0001). This combined molecular classifier was further validated on an independent cohort of 84 children with HR-ALL (P = 0.006). Conclusions. Molecular classifiers predictive of RFS and MRD can be used to distinguish distinct prognostic groups within HR-ALL, significantly improving risk classification schemes and the ability to prospectively identify children at diagnosis who will respond to or fail current treatment regimens. NOTE: Due to Children's Oncology Group (COG) restrictions, outcome and MRD data cannot be provided as part of the covariate data for this dataset at the present time. If you would like to arrange individual access to this data, please contact COG or the PI of this study, Dr. Cheryl Willman, at the University of New Mexico Cancer Center (cwillman@unm.edu) to arrange a collaboration.

Project description:PAPER 1:"Identification of novel subgroups of high-risk pediatric precursor B acute lymphoblastic leukemia (B-ALL) by unsupervised microarray analysis: clinical correlates and therapeutic implications. A Children's Oncology Group (COG) study." ABSTRACT We examined gene expression profiles of pre-treatment specimens from 207 patients from the COG P9906 study to identify signatures of children with high risk B-precursor acute lymphoblastic leukemia (ALL) and to determine whether the resulting clusters are associated with either specific clinical features or treatment response characteristics. Four unsupervised clustering methods were utilized to classify patients into similar groups. The different clustering algorithms showed significant overlap in cluster membership. Two clusters contained all cases with either t(1;19)(q23;p13) translocations or MLL rearrangements. The other six clusters were novel and had no recurring chromosomal abnormalities or distinctive clinical features. Members of two of these novel clusters had significant survival differences when compared to the overall 4-year relapse-free survival (RFS) of 61%. These included clusters of patients with either significantly better (94.7%) or worse (21.0%) RFS at 4 years. Children of Hispanic/Latino ethnicity were disproportionately present in the poor outcome cluster. The poor outcome cluster represents a novel biologically distinctive subset of B-precursor ALL that may occur at least as frequently as BCR/ABL. Further molecular characterization of this cluster may lead to the discovery of genomic abnormalities that can be targeted to improve the currently dismal outcome for children with this gene signature. The Sample data have also been used in another study: PAPER 2: "Gene expression classifiers for minimal residual disease and relapse free survival improve outcome prediction and risk classification in children with high risk acute lymphoblastic leukemia. A Children's Oncology Group study". ABSTRACT Background. Nearly 25% of children with B-precursor ALL present with "high-risk" disease (HR-ALL) that is resistant to current therapies. Gene expression profiling may yield molecular classifiers for outcome prediction that can be used to improve risk classification and therapeutic targeting. Methods. Expression profiles were obtained in pre-treatment leukemic samples from 207 uniformly treated children with HR-ALL. Relapse free survival (RFS) was 61% at 4 years and flow cytometric measures of minimal residual disease (MRD) at the end of induction (day 29) were predictive of outcome (P<0.001). Molecular classifiers predictive of RFS and MRD were developed using extensive cross-validation procedures. Results. A 38 gene molecular risk classifier predictive of RFS (MRC-RFS) distinguished two groups in HR-ALL with different relapse risks: low (4 yr RFS: 81%, n=109) vs. high (4 yr RFS: 50%, n=98) (P<0.0001). In multivariate analysis, the best predictor combined MRC-RFS and day 29 flow MRD data, classifying children into low (87% RFS), intermediate (62% RFS), or high risk (29% RFS) groups (P<0.0001). A 21 gene molecular classifier predictive of MRD could effectively substitute for day 29 flow MRD, yielding a combined classifier that similarly distinguished three risk groups at pre-treatment (low: 82% RFS; intermediate: 63% RFS; and high risk: 45% RFS) (P<0.0001). This combined molecular classifier was further validated on an independent cohort of 84 children with HR-ALL (P = 0.006). Conclusions. Molecular classifiers predictive of RFS and MRD can be used to distinguish distinct prognostic groups within HR-ALL, significantly improving risk classification schemes and the ability to prospectively identify children at diagnosis who will respond to or fail current treatment regimens. NOTE: Due to Children's Oncology Group (COG) restrictions, outcome and MRD data cannot be provided as part of the covariate data for this dataset at the present time. If you would like to arrange individual access to this data, please contact COG or the PI of this study, Dr. Cheryl Willman, at the University of New Mexico Cancer Center (cwillman@unm.edu) to arrange a collaboration. Unsupervised clustering and supervised risk classification analyses of 207 diagnostic samples and associated clinical covariate data. See the Summary for greater details. The data were analyzed using Microarray Suite version 5.0 (MAS 5.0) in the Affymetrix Gene Chip Operating Software Version 1.4. Probe masking was used (see 9906_TT207_Affymetrix_probe_mask.msk, linked below as a supplementary file). Otherwise all Affymetrix default parameter settings were used. Global scaling as the normalization method, with the default target intensity of 500, was used.

Dataset Information

Prospective randomized phase II study of FOLFIRI versus FOLFOX7 in advanced gastric adenocarcinoma: a Chinese Western Cooperative Gastrointestinal Oncology Group Study.

Publications

Prospective randomized phase II study of FOLFIRI versus FOLFOX7 in advanced gastric adenocarcinoma: a Chinese Western Cooperative Gastrointestinal Oncology Group Study.

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