Gene Expression Profile Test Research Articles

A Gene Expression Profile Test (EoGenius) Can Predict Subsequent Development of Histologic Eosinophilic Esophagitis in Patients with Non-diagnostic Index Biopsies

Introduction: The AGA consensus on eosinophilic esophagitis (EoE) requires a minimum of 15 eosinophils per high-power field (eos/HPF) to be counted in the squamous epithelium. Some patients with typical clinical signs and symptoms of EoE have low, non-diagnostic eosinophil counts in their esophageal biopsies, and above-threshold infiltrates become evident only at subsequent biopsies. A recently developed RNA gene expression profile test (EoGenius) has been shown to distinguish EoE from other conditions independently of the numbers of intraepithelial eosinophils (Dellon et al., 2016). Methods: Here we report 4 patients in whom EoE was clinically suspected, in spite of equivocal presentations. Their initial biopsies were reviewed and determined to be either non-diagnostic or at-threshold for histologic EoE. Within 3 to 6 months of the first biopsy, the patients had a follow-up endoscopy with esophageal biopsies that were diagnostic of EoE. We retrospectively performed the EoGenius test on the specimens from the first (negative) biopsy specimens to determine whether EoGenius could predict the subsequent development of histologic EoE. Results: Demographic and clinical data are summarized in Figure 1. T1 indicates the first biopsy on which EoGenius was performed. T2 indicated the follow-up biopsy. In patients A and B the biopsies were unequivocally negative for EoE (zero eos/HPF). In patient C the eosinophil count reached 15 eos/HPF, but sampling was exclusively from the distal esophagus at the gastroesophageal junction (GEJ), and there was neither eosinophilic degranulation nor microabscesses, making the diagnosis of EoE difficult to ascertain. Patient D had a diagnosis of EoE at the first biopsy based on the presence of 16 eos/HPF in the upper esophagus. However, there were neither eosinophilic degranulation nor microabscesses, and no samples from other parts of the esophagus were available, leaving the diagnosis tentative at best. In all patients the EoGenius test on the T1 biopsy specimens was positive.Figure 1Conclusions: If these results are confirmed by a large study, currently underway, then the results of EoGenius performed on non-diagnostic or equivocal esophageal biopsy specimens could be used to make informed management decisions. In a numbers of cases, the performance of a second EGD with biopsies within a short interval from the first one could be avoided, resulting in both risk reduction and financial advantages for patients and payers.

Rapid On Site Evaluation (ROSE) in Uveal Melanomas for Diagnostic Adequacy and Optimal Triaging for Molecular Gene Expression Profile (GEP) Testing: A Series Analysis of 67 Cases

Rapid On Site Evaluation (ROSE) in Uveal Melanomas for Diagnostic Adequacy and Optimal Triaging for Molecular Gene Expression Profile (GEP) Testing: A Series Analysis of 67 Cases

Jagged1 expression by osteoblast-lineage cells regulates trabecular bone mass and periosteal expansion in mice

Loss-of-function mutations in the Notch ligand, Jagged1 (Jag1), result in multi-system developmental pathologies associated with Alagille syndrome (ALGS). ALGS patients present with skeletal manifestations including hemi-vertebrae, reduced bone mass, increased fracture incidence and poor bone healing. However, it is not known whether the increased fracture risk is due to altered bone homeostasis (primary) or nutritional malabsorption due to chronic liver disease (secondary). To determine the significance of Jag1 loss in bone, we characterized the skeletal phenotype of two Jag1-floxed conditional knockout mouse models: Prx1-Cre;Jag1f/f to target osteoprogenitor cells and their progeny, and Col2.3-Cre;Jag1f/f to target mid-stage osteoblasts and their progeny. Knockout phenotypes were compared to wild-type (WT) controls using quantitative micro-computed tomography, gene expression profiling and mechanical testing. Expression of Jag1 and the Notch target genes Hes1 and Hey1 was downregulated in all Jag1 knockout mice. Osteoblast differentiation genes were downregulated in whole bone of both groups, but unchanged in Prx1-Cre;Jag1f/f cortical bone. Both knockout lines exhibited changes in femoral trabecular morphology including decreased bone volume fraction and increased trabecular spacing, with males presenting a more severe trabecular osteopenic phenotype. Prx1-Cre;Jag1f/f mice showed an increase in marrow mesenchymal progenitor cell number and, counterintuitively, developed increased cortical thickness resulting from periosteal expansion, translating to greater mechanical stiffness and strength. Similar alterations in femoral morphology were observed in mice with canonical Notch signaling disrupted using Prx1-Cre-regulatable dominant-negative mastermind like-protein (dnMAML). Taken together, we report that 1) Jag1 negatively regulates the marrow osteochondral progenitor pool, 2) Jag1 is required for normal trabecular bone formation and 3) Notch signaling through homotypic Jag1 signaling in osteochondral progenitors, but not mature osteoblasts, inhibits periosteal expansion. Therefore, Jag1 signaling within the osteoblast lineage regulates bone metabolism in a compartment-dependent manner. Moreover, loss of Jag1 function in osteoblast lineage cells may contribute to the skeletal phenotype associated with ALGS.

Clinical impact of a 31-gene expression profile test for cutaneous melanoma in 156 prospectively and consecutively tested patients

Objective: DecisionDx-Melanoma* is a 31-gene expression profile test that predicts the risk of metastasis in patients with primary cutaneous melanoma (CM). This study was designed to ascertain clinical management changes determined by the test outcome, which classifies CM patients being at low (Class 1) or high (Class 2) risk for recurrence.Research design and methods: Medical charts were reviewed from 156 CM patients from six institutions (three dermatology and three surgical oncology practices) who were consecutively tested between May 2013 and December 2015. Clinical management data that were compiled and compared before and after receipt of the 31-gene expression test result included frequency of physical exams, frequency and modality of imaging, and referrals to surgical and medical oncologists.Results: Forty-two percent of patients were Stage I, 47% were Stage II and 8% were Stage III. Overall, 95 patients (61%) were Class 1 and 61 (39%) were Class 2. Documented changes in management were observed in 82 (53%) patients, with the majority of Class 2 patients (77%) undergoing management changes compared to 37% of Class 1 patients (p < 0.0001 by Fisher’s exact test). The majority (77/82, 94%) of these changes were concordant with the risk indicated by the test result (p < 0.0001 by Fisher’s exact test), with increased management intensity for Class 2 patients and reduced management intensity for Class 1 patients.Conclusions: Molecular risk classification by gene expression profiling has clinical impact and influences physicians to direct clinical management of CM patients. The vast majority of the changes implemented after the receipt of test results were reflective of the low or high recurrence risk associated with the patient’s molecular classification. Because follow-up data was not collected for this patient cohort, the study is limited for the assessment of the impact of gene expression profile based management changes on healthcare resource utilization and patient outcome.

Prospective validation of gene expression profiling in primary cutaneous melanoma.

9565Background: Gene expression profiling (GEP) is becoming an integral part of treatment decision making in cancer. A GEP test (DecisionDx-Melanoma) has been in commercial use based on data from m...

The influence of gene expression profiling on decisional conflict in decision making for early-stage breast cancer chemotherapy

BackgroundWomen with early-stage breast cancer, of whom only 15% will experience a recurrence, are often conflicted or uncertain about taking chemotherapy. Gene expression profiling (GEP) of tumours informs risk prediction, potentially affecting treatment decisions. We examined whether receiving a GEP test score reduces decisional conflict in chemotherapy treatment decision making. MethodsA general population sample of 200 women completed the decisional conflict scale (DCS) at baseline (no GEP test score scenario) and after (scenario with GEP test score added) completing a discrete choice experiment survey for early-stage breast cancer chemotherapy. We scaled the 16-item DCS total scores and subscores from 0 to 100 and calculated means, standard deviations and change in scores, with significance (p < 0.05) based on matched pairs t-tests. ResultsWe identified five respondent subgroups based on preferred treatment option; almost 40% did not change their chemotherapy decision after receiving GEP testing information. Total score and all subscores (uncertainty, informed, values clarity, support, and effective decision) decreased significantly in the respondent subgroup who were unsure about taking chemotherapy initially but changed to no chemotherapy (n =33). In the subgroup of respondents (n = 25) who chose chemotherapy initially but changed to unsure, effective decision subscore increased significantly. In the overall sample, changes in total and all subscores were non-significant. ConclusionsGEP testing adds value for women initially unsure about chemotherapy treatment with a decrease in decisional conflict. However, for women who are confident about their treatment decisions, GEP testing may not add value. Decisions to request GEP testing should be personalised based on patient preferences.

PCN120 - Gene Expression Profile Testing in Uveal Melanoma: An Economic Model to Evaluate Resource use in the United States

Nearly 50% of all uveal melanoma patients will metastasize within five years, predominantly to the liver, despite only 4% presenting with metastatic disease at diagnosis. Early detection through surveillance thus becomes paramount. DecisionDx-UM is a validated prognostic gene expression profile test that categorizes a patient’s metastatic risk as low, medium or high, allowing them to be followed with a surveillance program of corresponding intensity and minimizing over- or under-treatment. A decision tree model was developed to assess the impact of DecisionDx-UM on resource utilization associated with metastatic surveillance. Surveillance costs (outpatient visits, liver function testing, and imaging) were compared for the previous framework in which all patients received high-intensity surveillance regimens, and the current scenario in which patients are tested with DecisionDx-UM and receive a low-, medium- or high-intensity regimen based on their individual risk. Regimens and model structure were based on literature review and US clinical practice; cost inputs were based on 2015 Medicare rates. The model assumes 2,500 diagnoses per year and survival rates for each risk group based on results of the first Cooperative Ocular Oncology Group study. Model predictions included cost savings and reduction in surveillance procedures. DecisionDx-UM was associated with a 50% reduction in the number of surveillance procedures performed at two years compared to the previous framework (21,907 procedures with DecisionDx-UM vs. 43,706 without), with an overall 63% reduction at five years (40,496 procedures with DecisionDx-UM vs. 109,266 without). Overall cost savings per patient was $2,121 with total cost savings of $18,205,902 at five years. Use of DecisionDx-UM has the potential to greatly reduce resource utilization in uveal melanoma, allowing clinicians to focus aggressive surveillance programs on high-risk patients most likely to benefit from these interventions while sparing low-risk patients. This can also result in meaningful cost savings for payers in the US.

Cost-effectiveness of using a gene expression profiling test to aid in identifying the primary tumour in patients with cancer of unknown primary.

We aimed to investigate the cost-effectiveness of a 2000-gene-expression profiling (GEP) test to help identify the primary tumor site when clinicopathological diagnostic evaluation was inconclusive in patients with cancer of unknown primary (CUP). We built a decision-analytic-model to project the lifetime clinical and economic consequences of different clinical management strategies for CUP. The model was parameterized using follow-up data from the Manitoba Cancer Registry, cost data from Manitoba Health administrative databases and secondary sources. The 2000-GEP-based strategy compared to current clinical practice resulted in an incremental cost-effectiveness ratio (ICER) of $44,151 per quality-adjusted life years (QALY) gained. The total annual-budget impact was $36.2 million per year. A value-of-information analysis revealed that the expected value of perfect information about the test's clinical impact was $4.2 million per year. The 2000-GEP test should be considered for adoption in CUP. Field evaluations of the test are associated with a large societal benefit.

Impact of stroma LOXL2 overexpression on the prognosis of intrahepatic cholangiocarcinoma

BackgroundIntrahepatic cholangiocarcinoma (ICC) is associated with a poor prognosis related to early recurrence especially in the remnant liver after surgery. ICC exhibits a dense desmoplastic stroma which plays a pivotal role in ICC aggressiveness. Thus, analyzing gene deregulation in the stroma of ICC may help to identify new prognosis biomarkers and promising therapeutic targets. The aim of this study was to evaluate the clinical relevance of the matrix-remodeling enzyme lysyl oxidase-like 2 (LOXL2) expression in ICC. Material and methodsLOXL2 messenger RNA levels were evaluated in microdissected tumoral stroma (TS) and in nontumoral fibrous tissue by gene expression profiling (testing set, n = 10) obtained from gene expression omnibus database and by quantitative real time polymerase chain reaction (validating set, n = 6). LOXL2 protein levels were evaluated by immunohistochemistry on a tissue microarray containing 80 independent patients. The relationship between LOXL2 expression and survival was assessed by univariate and multivariate analyses. ResultsLOXL2 messenger RNA levels were increased in TS, both in the testing and the validating sets (P < 0.01). These results were confirmed at a protein level, with a significantly higher LOXL2 immunostaining in TS (P < 0.01). Univariate analysis revealed that LOXL2 expression was correlated with a poor overall survival and disease-free survival (P < 0.01). Importantly, high expression of LOXL2 was an independent prognostic factor of worst overall survival (hazard ratio = 5.29, confidence interval [CI] 95% = 1.71-16.3, P < 0.01) and disease-free survival (hazard ratio = 5.55, CI 95% = 2.14-14.37, P < 0.01). ConclusionsOur study provides additional arguments for a role of extracellular matrix remodeling in ICC aggressiveness and identifies LOXL2 as a new prognostic marker and a promising therapeutic target in ICC.

Tumor-height regression rate after brachytherapy between choroidal melanoma gene expression profile classes: effect of controlling for tumor height.

To evaluate the relationship between choroidal melanoma regression rate and its gene expression profile class after iodine-125 brachytherapy at 3 and 6months, controlling for baseline tumor height. Patients from October 2012 to January 2015 at a single Ophthalmic Oncology Center who had undergone iodine-125 brachytherapy for the treatment of choroidal melanoma and who had a gene expression profile test result obtained from intraoperative fine-needle aspiration biopsy at the time of plaque surgery were retrospectively reviewed. Baseline patient and tumor characteristics were obtained, including tumor height and gene expression profile test result. Tumor height at 3 and 6months following treatment was obtained. Regression rate was analyzed with two-way analysis of variance to class type and baseline pre-operative tumor height. Class 2 patients were matched to class 1 patients by tumor height and resulting distributions of paired regression rate differences were compared. A total of 114 patients were studied. When preoperative tumor height was controlled for in the comparative analysis, neither group of patients at 3 or 6months had a significant dependency between gene expression profile class and tumor regression rate. Additionally, class 1 and class 2 patients matched for pre-operative tumor height did not express different regression rates. Our study adds to a growing body of evidence that tumor regression rate does not necessarily depend on gene expression profile class type in choroidal melanoma after brachytherapy at 3 and 6months when controlling for baseline tumor height.

Gene expression profiling identifies responsive patients with cancer of unknown primary treated with carboplatin, paclitaxel, and everolimus: NCCTG N0871 (alliance)

Carboplatin (C) and paclitaxel (P) are standard treatments for carcinoma of unknown primary (CUP). Everolimus, an mTOR inhibitor, exhibits activity in diverse cancer types. We did a phase II trial combining everolimus with CP for CUP. We also evaluated whether a gene expression profiling (GEP) test that predicts tissue of origin (TOO) could identify responsive patients. A tumor biopsy was required for central confirmation of CUP and GEP. Patients with metastatic, untreated CUP received everolimus (30 mg weekly) with P (200 mg/m(2)) and C (area under the curve 6) every 3 weeks. The primary end point was response rate (RR), with 22% needed for success. The GEP test categorized patients into two groups: those having a TOO where CP is versus is not considered standard therapy. Of 45 assessable patients, the RR was 36% (95% confidence interval 22% to 51%), which met criteria for success. Grade ≥3 toxicities were predominantly hematologic (80%). Adequate tissue for GEP was available in 38 patients and predicted 10 different TOOs. Patients with a TOO where platinum/taxane is a standard (n = 19) tended to have higher RR (53% versus 26%) and significantly longer PFS (6.4 versus 3.5 months) and OS (17.8 versus 8.3 months, P = 0.005), compared with patients (n = 19) with a TOO where platinum/taxane is not standard. Everolimus combined with CP demonstrated promising antitumor activity and an acceptable side-effect profile. A tumor biomarker identifying TOO may be useful to select CUP patients for specific antitumor regimens. NCT00936702.

Clinical usefulness of gene-expression profile to rule out acute rejection after heart transplantation: CARGO II.

AimsA non-invasive gene-expression profiling (GEP) test for rejection surveillance of heart transplant recipients originated in the USA. A European-based study, Cardiac Allograft Rejection Gene Expression Observational II Study (CARGO II), was conducted to further clinically validate the GEP test performance.Methods and resultsBlood samples for GEP testing (AlloMap®, CareDx, Brisbane, CA, USA) were collected during post-transplant surveillance. The reference standard for rejection status was based on histopathology grading of tissue from endomyocardial biopsy. The area under the receiver operating characteristic curve (AUC-ROC), negative (NPVs), and positive predictive values (PPVs) for the GEP scores (range 0–39) were computed. Considering the GEP score of 34 as a cut-off (>6 months post-transplantation), 95.5% (381/399) of GEP tests were true negatives, 4.5% (18/399) were false negatives, 10.2% (6/59) were true positives, and 89.8% (53/59) were false positives. Based on 938 paired biopsies, the GEP test score AUC-ROC for distinguishing ≥3A rejection was 0.70 and 0.69 for ≥2–6 and >6 months post-transplantation, respectively. Depending on the chosen threshold score, the NPV and PPV range from 98.1 to 100% and 2.0 to 4.7%, respectively.ConclusionFor ≥2–6 and >6 months post-transplantation, CARGO II GEP score performance (AUC-ROC = 0.70 and 0.69) is similar to the CARGO study results (AUC-ROC = 0.71 and 0.67). The low prevalence of ACR contributes to the high NPV and limited PPV of GEP testing. The choice of threshold score for practical use of GEP testing should consider overall clinical assessment of the patient's baseline risk for rejection.

Clinical Performance and Management Outcomes with the DecisionDx-UM Gene Expression Profile Test in a Prospective Multicenter Study.

Uveal melanoma management is challenging due to its metastatic propensity. DecisionDx-UM is a prospectively validated molecular test that interrogates primary tumor biology to provide objective information about metastatic potential that can be used in determining appropriate patient care. To evaluate the continued clinical validity and utility of DecisionDx-UM, beginning March 2010, 70 patients were enrolled in a prospective, multicenter, IRB-approved study to document patient management differences and clinical outcomes associated with low-risk Class 1 and high-risk Class 2 results indicated by DecisionDx-UM testing. Thirty-seven patients in the prospective study were Class 1 and 33 were Class 2. Class 1 patients had 100% 3-year metastasis-free survival compared to 63% for Class 2 (log rank test p = 0.003) with 27.3 median follow-up months in this interim analysis. Class 2 patients received significantly higher-intensity monitoring and more oncology/clinical trial referrals compared to Class 1 patients (Fisher's exact test p = 2.1 × 10−13 and p = 0.04, resp.). The results of this study provide additional, prospective evidence in an independent cohort of patients that Class 1 and Class 2 patients are managed according to the differential metastatic risk indicated by DecisionDx-UM. The trial is registered with Clinical Application of DecisionDx-UM Gene Expression Assay Results (NCT02376920).

Recommendations from the EGAPP Working Group: does the use of Oncotype DX tumor gene expression profiling to guide treatment decisions improve outcomes in patients with breast cancer?

of The Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group found insufficient evidence to recommend for or against the use of Oncotype DX testing to guide chemotherapy treatment decisions in women with hormone receptor-positive, lymph node-negative, or lymph node-positive early breast cancer who are receiving endocrine therapy. This recommendation statement updates a 2009 EGAPP statement on the use of gene expression profiling tests in breast cancer. Evidence of clinical validity for Oncotype DX was confirmed as adequate. With regard to clinical utility, although there was evidence from prospective retrospective studies that the Oncotype DX test predicts benefit from chemotherapy, and there was adequate evidence that the use of Oncotype DX gene expression profiling in clinical practice changes treatment decisions regarding chemotherapy, no direct evidence was found that the use of Oncotype DX testing leads to improved clinical outcomes. In women with early-stage invasive breast cancer, gene expression profiling is increasingly being used as an aid to estimate the likely benefit from chemotherapy treatment. In a previous recommendation statement, the EGAPP Working Group (EWG) found adequate evidence for clinical validity of some gene expression profiling tests in predicting distant disease recurrence in women with early-stage, hormone receptor-positive, lymph-node-negative breast cancer who are treated with tamoxifen, but insufficient evidence that use of these tests for decisions about chemotherapy treatment has clinical utility. The current recommendation statement updates these findings for Oncotype DX and extends them to the population of women with lymph node-positive disease, using evidence from recent systematic reviews and other sources. The previous recommendation statement found that evidence was inadequate to enable quantitative determination of the analytic validity of Oncotype DX. Analytic validity was not reconsidered in the updated recommendation statement because there remains no gold-standard test for comparison. The EWG found that new evidence published since the original evidence review supports the clinical validity of Oncotype DX in predicting risk of distant metastases in women with hormone receptor-positive, early-stage breast cancer that is either node-negative or node-positive. No direct evidence was found that use of Oncotype DX tumor gene expression profiling to guide treatment decisions improves clinical outcomes in women with early breast cancer. There is indirect evidence, from prospective retrospective studies on archived tissue samples from randomized controlled trials, that the Oncotype DX test can predict benefit from chemotherapy. Large, prospective, randomized, controlled trials currently in progress may provide evidence of clinical utility. Until definitive evidence for clinical utility is available, clinicians must decide on a case-by-case basis whether to offer the test to patients. Although Oncotype DX testing has been reported, on the basis of economic modeling studies, to be cost-effective in several different health-care systems and to save costs in the US health-care setting, studies were based on assumptions regarding the clinical utility of the test that require confirmation by clinical trial results.Genet Med 18 8, 770-779.

Cost-Effectiveness of Subtype-Based Treatment Strategies for Diffuse Large B-Cell Lymphoma Patients (DLBCL)

BACKGROUND Patients (pts) with DLBCL may have widely divergent outcomes despite harboring histologically similar tumors. Gene expression profiling (GEP) and immunohistochemistry (IHC) algorithms can assign pts to the germinal center B-cell-like (GCB) or activated B-cell-like (ABC) subtypes, with the latter carrying a less favorable prognosis. While IHC is widely available, GEP is more accurate in characterizing the exact subtype, however it is largely limited to academic institutions due to cost and feasibility. The addition of novel agents such as lenalidomide to the standard regimen of rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (RCHOP) demonstrates the potential to improve outcomes for ABC DLBCL compared to historical controls (Nowakowski et al. J Clin Oncol. 2015). We examined the cost-effectiveness of using subtype-specific treatment strategies compared to RCHOP with or without a novel agent.METHODS We developed a Markov model to compare cost and effectiveness of 3 treatment strategies for pts 18-65 years of age with newly diagnosed DLBCL: (1) administering RCHOP to all pts, (2) administering lenalidomide+RCHOP (R2CHOP) to all pts or (3) performing subtype testing and administering RCHOP to pts with GCB and R2CHOP to pts with ABC. We calculated the costs and effectiveness of each strategy based on a clinical scenario with data derived from Nowakowski et al. 2015. The model utilized GCB/non-GCB-specific overall survival (OS) and progression-free survival (PFS) data for historical controls treated with RCHOP (strategy 1), and data from pts treated with R2CHOP from the phase 2 study (strategy 2). Strategy 3 utilized RCHOP outcomes for GCB pts and R2CHOP outcomes for non-GCB pts. Next, we conducted an exploratory analysis comparing these strategies in a hypothetical scenario. We used composite PFS and OS survival curves from our previous systematic review (Read et al. CLML 2014) for GEP-defined GCB and ABC pts, respectively, with RCHOP (strategy 1), and assumed various hazard ratios (HRs) representing hypothetical improvements in PFS and OS by adding a novel agent to RCHOP for ABC pts and no benefit (HR=1) for GCB pts (strategy 2 and 3). In addition to the gold standard GEP test, we considered practical IHC testing with potential subtype misclassification. Health outcomes were measured in life years (LYs) and quality-adjusted life years (QALYs). Drug and administration costs were based on average wholesale price and 2015 Medicare physician fee schedule. Model robustness was addressed in probabilistic sensitivity analyses (PSAs).RESULTS. In clinical scenario analysis, Strategy 1 provided 5.2 QALYs (6.7 LYs) at a cost of $69,920; strategy 2 improved health outcomes by providing 6.5 QALYs (8.5 LYs) at a cost of $143,753; and the subtype-based strategy 3 provided the greatest benefit of 6.9 QALYs (8.8 LYs) at a cost of $97,200. The incremental cost-effectiveness ratio (ICER) for strategy 3 was $16,881/QALY ($13,340/LY) compared with standard RCHOP, and strategy 2 was dominated since subtype-based treatment was more effective and less costly. PSA demonstrated 99.7% probability that subtype-based treatment was the most cost-effective strategy, at a willingness-to-pay value of $50,000/QALY. In the hypothetical scenario, with HR of PFS and OS for ABC pts with novel treatment varying from 0.5 to 0.9, strategy 3 produced ICERs ranging from $16,971/QALY ($13,992/LY) to $123,509/QALY ($108,000/LY) when compared with RCHOP. Similar findings were observed for models involving IHC subtype testing (see Table).CONCLUSIONS. There are multiple subtype specific diagnostic and treatment strategies emerging for pts with DLBCL. The gains in QALYs and LYs, in addition to favorable ICERs suggest that subtype-specific treatment strategies for DLCBL can provide meaningful clinical benefit and value and should be explored in future trials.Table. Incremental cost-effectiveness of subtype-based treatment Table 1GEP test (sensitivity =specificity=1.00)IHC Hans algorithm (sensitivity=0.82, specificity=0.90)PFS/OS HR for ABCIncremental LYIncremental QALYICER($/QALY)Incremental LYIncremental QALYICER($/QALY)Nowakowski et al. 2015 HR(PFS)=0.35, HR(OS)=0.242.422.016,9712.201.8120,526HR=0.5 (OS/PFS)1.741.4920,2551.591.3525,047HR=0.7 (OS/PFS)0.970.8336,4750.880.7645,015HR=0.9 (OS/PFS)0.280.25123,5090.260.23148,391 DisclosuresFlowers:Gilead: Research Funding; Spectrum: Research Funding; Roche: Other: unpaid consultant; Biogen Idec: Other: unpaid consultant; Optum Rx: Consultancy; Algeta: Consultancy; Millennium/Takeda: Research Funding; Abbott: Research Funding; Celgene: Other: unpaid consultant, Research Funding; Genentech: Other: unpaid consultant, Research Funding.

Independent Prognostic Significance of Gene Expression Profile Class and Largest Basal Diameter of Posterior Uveal Melanomas

To determine whether any conventional clinical prognostic factors for metastasis from uveal melanoma retain prognostic significance in multivariate models incorporating gene expression profile (GEP) class of the tumor cells. Prospective, interventional case series with a prognostic model. Single-institution study of GEP testing and other conventional prognostic factors for metastasis and metastatic death in 299 patients with posterior uveal melanoma evaluated by fine-needle aspiration biopsy (FNAB) at the time of or shortly prior to initial treatment. Univariate prognostic significance of all evaluated potential prognostic variables (patient age, largest linear basal diameter of tumor [LBD], tumor thickness, intraocular location of tumor, melanoma cytomorphologic subtype, and GEP class) was performed by comparison of Kaplan-Meier event rate curves and univariate Cox proportional hazards modeling. Multivariate prognostic significance of combinations of significant prognostic factors identified by univariate analysis was performed using step-up and step-down Cox proportional hazards modeling. GEP class was the strongest prognostic factor for metastatic death in this series. However, tumor LBD, tumor thickness, and intraocular tumor location also proved to be significant individual prognostic factors in this study. On multivariate analysis, a 2-term model that incorporated GEP class and largest basal diameter was associated with strong independent significance of each of the factors. Although GEP test is the most robust prognostic indicator in uveal melanoma and early studies of mostly larger tumors found that no clinicopathologic factors had significant prognostic value independent of GEP, our single-center study, which included a substantial proportion of smaller tumors, showed that both GEP and LBD of the tumor are independent prognostic factors for metastasis and metastatic death in multivariate analysis.

Performance of gene-expression profiling test score variability to predict future clinical events in heart transplant recipients.

BackgroundA single non-invasive gene expression profiling (GEP) test (AlloMap®) is often used to discriminate if a heart transplant recipient is at a low risk of acute cellular rejection at time of testing. In a randomized trial, use of the test (a GEP score from 0–40) has been shown to be non-inferior to a routine endomyocardial biopsy for surveillance after heart transplantation in selected low-risk patients with respect to clinical outcomes. Recently, it was suggested that the within-patient variability of consecutive GEP scores may be used to independently predict future clinical events; however, future studies were recommended. Here we performed an analysis of an independent patient population to determine the prognostic utility of within-patient variability of GEP scores in predicting future clinical events.MethodsWe defined the GEP score variability as the standard deviation of four GEP scores collected ≥315 days post-transplantation. Of the 737 patients from the Cardiac Allograft Rejection Gene Expression Observational (CARGO) II trial, 36 were assigned to the composite event group (death, re-transplantation or graft failure ≥315 days post-transplantation and within 3 years of the final GEP test) and 55 were assigned to the control group (non-event patients). In this case-controlled study, the performance of GEP score variability to predict future events was evaluated by the area under the receiver operator characteristics curve (AUC ROC). The negative predictive values (NPV) and positive predictive values (PPV) including 95 % confidence intervals (CI) of GEP score variability were calculated.ResultsThe estimated prevalence of events was 17 %. Events occurred at a median of 391 (inter-quartile range 376) days after the final GEP test. The GEP variability AUC ROC for the prediction of a composite event was 0.72 (95 % CI 0.6-0.8). The NPV for GEP score variability of 0.6 was 97 % (95 % CI 91.4-100.0); the PPV for GEP score variability of 1.5 was 35.4 % (95 % CI 13.5-75.8).ConclusionIn heart transplant recipients, a GEP score variability may be used to predict the probability that a composite event will occur within 3 years after the last GEP score.Trial registrationClinicaltrials.gov identifier NCT00761787Electronic supplementary materialThe online version of this article (doi:10.1186/s12872-015-0106-1) contains supplementary material, which is available to authorized users.

Adoption of Gene Expression Profiling for Breast Cancer in US Oncology Practice for Women Younger Than 65 Years.

A number of practice guidelines incorporate the use of gene expression profiling (GEP) tests for early-stage, hormone receptor-positive, HER2-negative breast tumors. Few studies describe factors associated with GEP testing in US oncology practice. We assessed the relationship between clinical, demographic, and group-level socioeconomic variables and test use in women younger than 65 years. Data from 5 state cancer registries were linked with insurance claims data and GEP test results. We assessed rates of testing and variables associated with test use in an incident cohort of 9,444 commercially insured women younger than 65 years, newly diagnosed with stage I or II hormone receptor-positive breast cancer from 2006 through 2012. Rates of testing for women with N0 disease increased from 20.4% in 2006 to 35.2% in 2011. Variables associated with higher rates of testing, beyond clinical factors such as nodal status (P<.001), included being diagnosed from 2008 through 2012 versus 2006 through 2007 (adjusted odds ratio [OR], 1.67; 95% CI, 1.47-1.90), having preexisting comorbidities (adjusted OR, 1.35; 95% CI, 1.14-1.59), and higher out-of-pocket pharmacy costs (adjusted OR, 1.66; 95% CI, 1.40-1.97). Women younger than 50 years were more likely to be tested if they had stage I versus stage II disease (P<.0001). In an insured population of women younger than 65 years, GEP testing increased after its inclusion in clinical practice guidelines and mounting evidence. Additional research is needed to better understand oncologists' decision not to order GEP testing for their patients who are otherwise eligible.

Population-based study of the effect of gene expression profiling on adjuvant chemotherapy use in breast cancer patients under the age of 65 years.

Gene expression profiling (GEP) testing can help to predict the risk of cancer recurrence and guide decisions about adjuvant chemotherapy for breast cancer (BC). However, no prior US studies have evaluated the relation between GEP testing and the use of adjuvant chemotherapy by women treated in a general oncology practice. Eligible patients were women under the age 65 of years who were newly diagnosed with their first stage I or II, hormone receptor-positive BC between 2006 and 2011 (n = 9405). This retrospective study was conducted with a data set consisting of registry data, health claims data, and GEP testing results. The distribution of GEP test results was reported in terms of the risk of recurrence predicted, and logistic regression was used to assess the association of test results with chemotherapy use, with adjustments made for multiple patient characteristics. The proportions of tested women with low, intermediate, and high recurrence score results were 51%, 39%, and 10%, respectively. Among these women, 11%, 47%, and 88%, respectively, received adjuvant chemotherapy. There was a significant, positive linear relation of assay scores with chemotherapy use within the low and intermediate subgroups after adjustments for all other factors (adjusted odds ratios, 1.17 and 1.20, respectively). Adjuvant chemotherapy use after GEP testing is generally consistent with the recommended test interpretation for women with a high or low predicted risk of recurrence. Chemotherapy use in the intermediate-risk group increased with Recurrence Score values, and evidence from ongoing randomized trials may help to clarify whether this finding reflects optimal interpretation of GEP test results. These results demonstrate the principle that genomic testing, on the basis of research establishing its utility, can be applied appropriately in general practice in accordance with guideline recommendations.

Economic Impact of Gene Expression Profiling in Patients with Early-Stage Breast Cancer in France.

Background and AimsThe heterogeneous nature of breast cancer can make decisions on adjuvant chemotherapy following surgical resection challenging. Oncotype DX is a validated gene expression profiling test that predicts the likelihood of adjuvant chemotherapy benefit in early-stage breast cancer. The aim of this study is to determine the costs of chemotherapy in private hospitals in France, and evaluate the cost-effectiveness of Oncotype DX from national insurance and societal perspectives.MethodsA multicenter study was conducted in seven French private hospitals, capturing retrospective data from 106 patient files. Cost estimates were used in conjunction with a published Markov model to assess the cost-effectiveness of using Oncotype DX to inform chemotherapy decision making versus standard care. Sensitivity analyses were performed.ResultsThe cost of adjuvant chemotherapy in private hospitals was estimated at EUR 8,218 per patient from a national insurance perspective and EUR 10,305 from a societal perspective. Cost-effectiveness analysis indicated that introducing Oncotype DX improved life expectancy (+0.18 years) and quality-adjusted life expectancy (+0.17 QALYs) versus standard care. Oncotype DX was found cost-effective from a national insurance perspective (EUR 2,134 per QALY gained) and cost saving from a societal perspective versus standard care. Inclusion of lost productivity costs in the modeling analysis meant that costs for eligible patients undergoing Oncotype DX testing were on average EUR 602 lower than costs for those receiving standard care.ConclusionsAs Oncotype DX was found both cost and life-saving from a societal perspective, the test was considered to be dominant to standard care. However, the delay in coverage has the potential to erode the quality of the French healthcare system, thus depriving patients of technologies that could improve clinical outcomes and allow healthcare professionals to better allocate hospital resources to improve the standard of care for all patients.