Delays in postremission chemotherapy for Philadelphia chromosome negative acute lymphoblastic leukemia are associated with inferior outcomes in patients who undergo allogeneic transplant: An analysis from ECOG 2993/MRC UK ALLXII

Adults with acute lymphoblastic leukemia (ALL) have a poorer prognosis than children due to a high risk of relapse. One explanation may be variable adherence to dose-intense chemotherapy. However, little is known about risk factors for delays in therapy and their impact on survival. We conducted an analysis of ECOG 2993/UKALLXII trial to study delays in postremission chemotherapy in adults with newly diagnosed ALL. Logistic regression was used to identify risk factors for a very long delay (VLD, >4 weeks) in start of intensification therapy. Cox regression was used to evaluate the impact of delays on overall survival (OS) and event-free survival (EFS). We evaluated 1076 Philadelphia chromosome negative (Ph−) patients who completed induction chemotherapy, achieved complete remission, and started intensification. Factors independently associated with VLD included duration of hospitalization (odds ratio [OR] = 1.2, P < 0.001) during Phase I; thrombocytopenia during Phase I (OR = 1.16, P = 0.004) or Phase II (OR 1.13, P = 0.001); chemotherapy dose reductions during Induction Phase I (OR = 1.72, P < 0.014); female sex (OR = 1.53, P = 0.010); Black (OR = 3.24, P = 0.003) and Asian (OR = 2.26, P = 0.021) race; and increasing age (OR = 1.31, P < 0.001). In multivariate Cox regression, patients who underwent allogeneic stem cell transplant (alloHCT) had significantly worse OS (HR 1.4, P = 0.03) and EFS (HR 1.4, P = 0.02) after experiencing a VLD compared to alloHCT patients who experienced ≤4 weeks delay. Specific populations (female, older, Black, and Asian patients) were more likely to experience delays in chemotherapy, as were those with significant toxicity during induction. VLDs in therapy negatively affected outcomes in patients undergoing allografting

The effect of imputed values on the distribution of the goodness-of-fit chi-square statistic

A method used to compensate for nonresponse is to impute missing values; that is, to replace each missing value with a respondent value selected from all observed values or from a subset of observed values. The imputation procedure used in this paper selects imputed values from the respondent data using simple random sampling with replacement within homogeneous subsets and replaces the missing values with these values to complete the data set. The empirical distribution of the goodness-of-fit chi-square statistic computed from the `completed' data set is compared to its asymptotic distribution and to the distribution of the traditional chi-square test statistic applied to the completed data set by ignoring the imputation.At nominal levels of five and ten percent, the asymptotic distribution of the goodness-of-fit chi-square statistic computed from the completed data set is shown to have a good empirical behavior at moderate sample sizes. When the imputed values are treated as actual responses and the imputation is ignored, the empirical levels of significance are much larger than the nominal levels.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/26909/1/0000475.pd

Thin Melanoma with Nodal Involvement: Analysis of Demographic, Pathologic, and Treatment Factors with Regard to Prognosis.

BACKGROUND: Although only a small proportion of thin melanomas result in lymph node metastasis, the abundance of these lesions results in a relatively large absolute number of patients with a diagnosis of nodal metastases, determined by either sentinel lymph node (SLN) biopsy or clinical nodal recurrence (CNR). METHODS: Independent cohorts with thin melanoma and either SLN metastasis or CNR were identified at two melanoma referral centers. At both centers, SLN metastasis patients were included. At center 1, the CNR cohort included patients with initial negative clinical nodal evaluation followed by CNR. At center 2, the CNR cohort was restricted to those presenting in the era before the use of SLN biopsy. Uni- and multivariable analyses of melanoma-specific survival (MSS) were performed. RESULTS: At center 1, 427 CNR patients were compared with 91 SLN+ patients. The 5- and 10-year survival rates in the SLN group were respectively 88 and 84 % compared with 72 and 49 % in the CNR group (p \u3c 0.0001). The multivariate analysis showed age older than 50 years (hazard ratio [HR] 1.5; 95 % confidence interval [CI] 1.2-1.9), present ulceration (HR 1.9; 95 % CI 1.2-2.9), unknown ulceration (HR 1.6; 95 % CI 1.3-2.1), truncal site (HR 1.6; 95 % CI 1.2-2.2), and CNR (HR 3.3; 95 % CI 1.8-6.0) to be associated significantly with decreased MSS (p \u3c 0.01 for each). The center 2 cohort demonstrated remarkably similar findings, with a 5-year MSS of 88 % in the SLN (n = 29) group and 76 % in the CNR group (n = 39, p = 0.09). CONCLUSION: Patients with nodal metastases from thin melanomas have a substantial risk of melanoma death. This risk is lower among patients whose disease is discovered by SLN biopsy rather than CNR

Should tumor VEGF expression influence decisions on combining low-dose chemotherapy with antiangiogenic therapy? Preclinical modeling in ovarian cancer

Because of its low toxicity, low-dose (LD) chemotherapy is ideally suited for combination with antiangiogenic drugs. We investigated the impact of tumor vascular endothelial growth factor A (VEGF-A) expression on the efficacy of LD paclitaxel chemotherapy and its interactions with the tyrosine kinase inhibitor SU5416 in the ID8 and ID8-Vegf models of ovarian cancer. Functional linear models using weighted penalized least squares were utilized to identify interactions between Vegf, LD paclitaxel and antiangiogenic therapy. LD paclitaxel yielded additive effects with antiangiogenic therapy against tumors with low Vegf expression, while it exhibited antagonism to antiangiogenic therapy in tumors with high Vegf expression. This is the first preclinical study that models interactions of LD paclitaxel chemotherapy with antiangiogenic therapy and tumor VEGF expression and offers important lessons for the rational design of clinical trials

Statistical methods for building better biomarkers of chronic kidney disease

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149268/1/sim8091.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149268/2/sim8091_am.pd

Monitoring melanoma recurrence with circulating tumor DNA: a proof of concept from three case studies

Background: A significant number of melanoma patients experience recurrence to distant sites, despite having had surgical treatment of the primary lesion, with curative intent. Monitoring of patients for early evidence of disease recurrence would significantly improve management of the disease, allowing timely therapeutic intervention. Circulating tumor DNA (ctDNA) is becoming a well-recognized biomarker for monitoring malignancies and has, in a few studies, been shown to signify disease recurrence earlier than conventional methods. Methods: We performed a retrospective analysis of plasma ctDNA using droplet digital PCR (ddPCR) in 30 primary melanoma patients with tumors harboring BRAF, NRAS or TERT promoter mutations. Mutant specific ctDNA, measured during clinical disease course, was compared with disease status in patients with confirmed disease recurrence (n = 3) and in those with no evidence of disease recurrence (n = 27). Results: Mutant specific ctDNA was detected in all three patients with disease recurrence at the time of clinically confirmed progression. In one case, plasma ctDNA detection preceded clinical identification of recurrence by an interval of 4 months. CtDNA was not detected in patients who were asymptomatic and had no radiological evidence of recurrence. Conclusions: This study demonstrates promising results for the use of ctDNA as an informative monitoring tool for melanoma patients having undergone tumor resection of an early stage primary tumor. The clinical utility of ctDNA for monitoring disease recurrence warrants investigation in prospective studies as it may improve patient outcome

A modified integrated genetic model for risk prediction in younger patients with acute myeloid leukemia

Background: Although cytogenetics-based prognostication systems are well described in acute myeloid leukemia (AML), overall survival (OS) remains highly variable within risk groups. An integrated genetic prognostic (IGP) model using cytogenetics plus mutations in nine genes was recently proposed for patients ≤60 years to improve classification. This model has not been validated in clinical practice. Methods and Findings: We retrospectively studied 197 patients with newly diagnosed de novo AML. We compared OS curves among the mutational profiles defined by the IGP model. The IGP model assigned patients with intermediate cytogenetics as having favorable, intermediate or unfavorable mutational profiles. The IGP model reassigned 50 of 137 patients with intermediate cytogenetics to favorable or unfavorable mutational profiles. Median OS was 2.8 years among 14 patients with intermediate cytogenetics and favorable mutational profiles (mutant NPM1 and mutant IDH1 or IDH2) and 1.3 years among patients with intermediate mutational profiles. Among patients with intermediate cytogenetics labeled as having unfavorable mutational profiles, median OS was 0.8 years among 24 patients with FLT3-ITD positive AML and high-risk genetic changes (trisomy 8, TET2 and/or DNMT3A) and 1.7 years among 12 patients with FLT3-ITD negative AML and high-risk mutations (TET2, ASXL1 and/or PHF6). OS for patients with intermediate cytogenetics and favorable mutational profiles was similar to OS for patients with favorable cytogenetics (p = 0.697) and different from patients with intermediate cytogenetics and intermediate mutational profiles (p = 0.028). OS among patients with FLT3-ITD positive AML and high-risk genetic changes was similar to patients with unfavorable cytogenetics (p = 0.793) and different from patients with intermediate IGP profile (p = 0.022). Patients with FLT3-ITD negative AML and high-risk mutations, defined as 'unfavorable' in the IGP model, had OS similar to patients with intermediate IGP profile (p = 0.919). Conclusions: The IGP model was not completely validated in our cohort. However, mutations in six out of the nine genes can be used to characterize survival (NPMI, IDH1, IDH2, FLT3-ITD, TET2, DNMT3A) and allow for more robust prognostication in the patients who are re-categorized by the IGP model. These mutations should be incorporated into clinical testing for younger patients outside of clinical trials, in order to guide therapy

DR6 as a Diagnostic and Predictive Biomarker in Adult Sarcoma

The Death Receptor 6 (DR6) protein is elevated in the serum of ovarian cancer patients. We tested DR6 serum protein levels as a diagnostic/predictive biomarker in several epithelial tumors and sarcomas.DR6 gene expression profiles were screened in publically available arrays of solid tumors. A quantitative immunofluorescent western blot analysis was developed to test the serum of healthy controls and patients with sarcoma, uterine carcinosarcoma, bladder, liver, and pancreatic carcinomas. Change in DR6 serum levels was used to assay the ability of DR6 to predict the response to therapy of sarcoma patients.DR6 mRNA is highly expressed in all tumor types assayed. Western blot analysis of serum DR6 protein demonstrated high reproducibility (r = 0.97). Compared to healthy donor controls, DR6 serum levels were not elevated in patients with uterine carcinosarcoma, bladder, liver, or pancreatic cancers. Serum DR6 protein levels from adult sarcoma patients were significantly elevated (p<0.001). This was most evident for patients with synovial sarcoma. Change in serum DR6 levels during therapy correlated with clinical benefit from therapy (sensitivity 75%, and positive predictive value 87%).DR6 may be a clinically useful diagnostic and predictive serum biomarker for some adult sarcoma subtypes.Diagnosis of sarcoma can be difficult and can lead to improper management of these cancers. DR6 serum protein may be a tool to aid in the diagnosis of some sarcomatous tumors to improve treatment planning. For patients with advanced disease, rising DR6 levels predict non-response to therapy and may expedite therapeutic decision making and reduce reliance on radiologic imaging

Cyclophosphamide- metabolizing enzyme polymorphisms and survival outcomes after adjuvant chemotherapy for node-positive breast cancer: a retrospective cohort study

Abstract Introduction Cyclophosphamide-based adjuvant chemotherapy is a mainstay of treatment for women with node-positive breast cancer, but is not universally effective in preventing recurrence. Pharmacogenetic variability in drug metabolism is one possible mechanism of treatment failure. We hypothesize that functional single nucleotide polymorphisms (SNPs) in drug metabolizing enzymes (DMEs) that activate (CYPs) or metabolize (GSTs) cyclophosphamide account for some of the observed variability in disease outcomes. Methods We performed a retrospective cohort study of 350 women enrolled in a multicenter, randomized, adjuvant breast cancer chemotherapy trial (ECOG-2190/INT-0121). Subjects in this trial received standard-dose cyclophosphamide, doxorubicin and fluorouracil (CAF), followed by either observation or high-dose cyclophosphamide and thiotepa with stem cell rescue. We used bone marrow stem cell-derived genomic DNA from archival specimens to genotype CYP2B6, CYP2C9, CYP2D6, CYP3A4, CYP3A5, GSTM1, GSTT1, and GSTP1. Cox regression models were computed to determine associations between genotypes (individually or in combination) and disease-free survival (DFS) or overall survival (OS), adjusting for confounding clinical variables. Results In the full multivariable analysis, women with at least one CYP3A4 *1B variant allele had significantly worse DFS than those who were wild-type *1A/*1A (multivariate hazard ratio 2.79; 95% CI 1.52, 5.14). CYP2D6 genotype did not impact this association among patients with estrogen receptor (ER) -positive tumors scheduled to receive tamoxifen. Conclusions These data support the hypothesis that genetic variability in cyclophosphamide metabolism independently impacts outcome from adjuvant chemotherapy for breast cancer