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Evaluating the merits of a genomic assay includes measuring analytic and clinical validity, and establishing clinical utility—a property that is not consistently defined. One definition of clinical utility that has gained traction is “the balance of benefits and harms associated with the use of the test in practice” [Genet Med. 2015; doi:10.1038/gim.2015.173]. The 21-gene RS assay is the only assay clinically validated for both prognosis and prediction of chemotherapy (CT) benefit in patients with node-negative (N0) or node-positive (N+), ER+, HER2− EBC. The original clinical validation studies were prospectively designed using archived tissue from legacy trials that had long-term outcomes (NSABP B-14 and B-20, TransATAC, and SWOG 8814). With 10+ years of the RS assay in clinical use, we now have real-world, prospective outcomes for patients with N0 or N+ disease that meet the aforementioned definition of clinical utility. Here we summarize the growing body of clinical evidence including the original validation studies, prospective outcomes-based trials, and analyses from two large, real-world registries in which patients were treated based on RS results: the US SEER and Clalit Health Services registries. The US SEER registry is a population-based cancer surveillance program that covers 30% of the US population and includes 40,134 N0 and 4,691 N+ patients with RS results. The Clalit Health Services registry, from the largest HMO in Israel, has 2,028 N0 and micrometastatic (Nmi) patients who were uniformly tested and had complete treatment information. In the SEER and Clalit cohorts, the distribution of RS results were similar for N0/Nmi and N+ patients: 54% and 57% low ( 5-y BC-specific Mortality (95% CI) SEER RegistriesClalit Registry N0a (N=38,568)Known CT use (% of N)N+b (N=4,691)Known CT use (% of N)N0/Nmic (N=2,028)Known CT use (% of N)RS In summary, after 10+ years of clinical use, the 21-gene RS assay has now amassed a body of clinical evidence from >50,000 patients that confirms the original clinical validation results and supports its clinical utility. The assay identifies patients with low RS results who can be safely and effectively treated with hormonal therapy alone and spared the toxicity of CT exposure. In aggregate, these data support the clinical utility of the 21-gene RS assay and its value to physicians and patients by providing information based on individual tumor biology that they can use to tailor treatment. Citation Format: Sing AP, Rothney M, Svedman C, Shak S, Baehner FL. Real-world clinical experience and outcomes in patients with early-stage breast cancer (EBC) treated according to the 21-gene recurrence score® (RS) result [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P6-09-08.

Background: The 21-Gene Recurrence Score® Assay (Oncotype DX®) has been validated as a prognostic and predictive tool in estrogen receptor (ER)+ breast cancer in multiple studies using archival specimens of clinical trials with long term follow up. Prospective outcome data from patients where treatment decisions incorporated the Recurrence Score results have not been reported. We evaluated treatments and clinical outcomes in patients undergoing Recurrence Score testing in 9 medical centers within Clalit Health Services (CHS), the largest HMO in Israel. Methods: Medical records of patients with N0/Nmic ER+ HER2-negative disease undergoing testing from 12/2004 to 12/2010 in 9 medical centers (Rabin, Lin, Soroka, Meir, Kaplan, Hadassah, Ha'emek, Rambam, and Shaare Zedek) within CHS were individually reviewed to verify treatments given, recurrence, and survival status. 5-year Kaplan-Meier (KM) and standard error estimates for distant recurrence and breast cancer specific survival were determined. Results: 1594 patients were evaluated with 5.9 years median follow-up. Median age, 61 (25-85) years; N0/Nmic (90%/10%); Grade I (16%), II (48%), III (16%), N/A (19%); histology, IDC (80%), lobular (13%), other (7%). Distribution of Recurrence Score risk groups (Recurrence Score results of Conclusions: These are the first prospective long term clinical outcome data from approximately 1600 patients for whom the 21-gene Recurrence Score assay has been incorporated in real-life clinical decision making. The documented use of CT was appropriately based on the Recurrence Score result, and the outcomes for recurrence and survival are consistent with previously reported prospective-retrospective studies of the 21-gene assay. The 5 year KM estimates for distant recurrence rate in patients with low and intermediate Recurrence Score results who were treated based upon their Recurrence Score results were very low (0.5% and 1.2%, respectively). Citation Format: Stemmer SM, Steiner M, Rizel S, Soussan-Gutman L, Geffen DB, Nisenbaum B, Ben-Baruch N, Isaacs K, Fried G, Rosengarten O, Uziely B, Svedman C, Rothney M, Klang SH, Ryvo L, Kaufman B, Evron E, Zidan J, Shak S, Liebermann N. Real-life analysis evaluating 1594 N0/Nmic breast cancer patients for whom treatment decisions incorporated the 21-gene recurrence score result: 5-year KM estimate for breast cancer specific survival with recurrence score results ≤30 is >98%. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P5-08-02.

ObjectivesTo evaluate the impact of the 12-gene Colon Cancer Recurrence Score Assay—a clinically validated prognosticator in stage II colon cancer after surgical resection—on adjuvant treatment decisions in T3 mismatch repair proficient (MMR-P) stage II colon cancer in clinical practice.MethodsThis retrospective analysis included all patients with T3 MMR-P stage II colon cancer (Clalit Health Services members) with Recurrence Score results (time frame January 2011 to May 2012). Treatment recommendations pretesting were compared with the treatments received. Changes were categorized as decreased (to observation alone/removing oxaliplatin from the therapy) or increased (from observation alone/adding oxaliplatin to the therapy) intensity.ResultsThe analysis included 269 patients; 58%, 32%, and 10% of the values were in the low (

Introduction The 21-gene Recurrence Score® assay (Oncotype DX®, Genomic Health, Inc.) is a validated predictor of recurrence risk/chemotherapy benefit in patients with estrogen receptor-positive (ER+) early-stage breast cancer treated with endocrine therapy. The Prosigna® assay (NanoString Technologies Inc.) is a validated prognosticator in postmenopausal patients with low-risk ER+ early-stage breast cancer treated with endocrine therapy. The assays were analytically/clinically developed and validated differently. This study focused on comparing recurrence risk estimates as determined by these assays and is the first blinded comparison of these assays on matched patient samples. Methods Sequential breast cancer specimens from postmenopausal, node-negative, ER+ patients treated at the Marin General Hospital were analyzed: first by the 21-gene assay then by the Prosigna assay in an independent lab blinded to the Recurrence Score results. Results The final analysis included 52 patients. Correlation between the Recurrence Score and the Prosigna assay results was poor (r = 0.08). Agreement between risk classifications based on these assays was 54%; 4/7 of patients classified as high risk by the Prosigna assay had low Recurrence Score results. Two tumors with high Recurrence Score results had low ER expression (close to positivity threshold); both of which had a low/intermediate Prosigna assay result. The Prosigna assay classified 73.1% and 23.1% of samples as luminal A and luminal B, respectively. A range of Recurrence Score results was observed within the subtypes; 83% of luminal B samples had a low Recurrence Score result. Conclusion Consistent with prior comparisons between the 21-gene and other genomic assays, our study demonstrated substantial differences in the way patients are risk stratified, suggesting that the different assays are not interchangeable. Funding Genomic Health, Inc. Electronic supplementary material The online version of this article (doi:10.1007/s12325-015-0269-2) contains supplementary material, which is available to authorized users.

Introduction The biopsy based 17-gene GPS was clinically validated to predict the likelihood of adverse surgical pathology in men with NCCN ® very low, low or low-intermediate risk prostate cancer. We performed a prospective study to assess the impact of incorporating GPS into treatment recommendations in 3 high volume urology practices. Methods Men with newly diagnosed prostate cancer meeting specific NCCN criteria were prospectively enrolled in the trial. Biopsy tissue was analyzed. Urologists indicated treatment recommendations on questionnaires administered before and after GPS. The primary study objectives were to assess all changes in treatment modality and/or treatment intensity after GPS. Results A total of 158 men were included in analysis, including 35, 71 and 52 at NCCN very low, low and low-intermediate risk. Biological risk predicted by GPS differed from NCCN clinical risk alone in 61 men (39%). Overall 18% of recommendations between active surveillance and immediate treatment changed after GPS. The relative increase in recommendations for active surveillance was 24% (absolute change 41% to 51%). In 41 of 158 men (26%) modality and/or intensity recommendations changed after GPS, including 25, 14 and 2 in whom recommendation intensity decreased, increased and were equivocal, respectively. All changes were directionally consistent with GPS. The NCCN low risk group showed the greatest absolute recommendation change after GPS (37%). In 17 of 57 men (30%) the initial recommendation of radical prostatectomy was changed to active surveillance after GPS. Urologists indicated greater confidence and found that incorporating GPS was useful in 85% and 79% of cases, respectively, including when biological risk confirmed the clinical risk category. Conclusions This study demonstrates that the 17-gene GPS influenced treatment recommendations among urologists and provided increased confidence in these recommendations in patients at NCCN very low to low-intermediate risk.

Intro Accurate measurement of ER in early stage invasive breast cancer (EBC) is important to identify patients likely to benefit from HT. While immunohistochemistry (IHC) is the most common method to quantify ER, other methods can also accurately measure ER, such as RT-PCR. ER is one of the genes included in the RT-PCR based 21-gene Recurrence Score assay (Oncotype DX®, Genomic Health, Redwood City, CA) and is also reported separately as a single gene expression. Additionally, the association between ER expression by RT-PCR (ER-PCR) and tamoxifen benefit has been reported by Kim, et al (2011). A recent study reported that patients with ER levels Aim The study aims are: (1) To correlate quantification of ER in EBC as assessed by Allred Score (AS) and ER as measured by RT-PCR in the 21-gene assay; (2) To describe changes in ER, Recurrence Score, and measures of proliferation after 2wks of an aromatase inhibitor (AI); (3) To perform exploratory analyses of factors associated with changes in proliferation. Methods 55 postmenopausal EBC patients with lower ER (AS 2-7) were treated with 2wks of an AI followed by wide excision. All patients had a 21-gene assay on a pre-and post-treatment (Tx) sample. Proliferation was measured by both Ki67 by IHC (in 45 patients) and by the proliferation gene group score (PGS) in the RT-PCR based 21-gene assay (in all patients). Proliferation response was defined by a 20% relative decrease in Ki67 or a decrease in PGS. Changes in proliferation were correlated with AS, ER-PCR and Recurrence Score result. Results The Table shows the correlation of AS with ER-PCR measured in the pre-Tx (r=0.83) samples. 94% of AS (2-3) patients and 56% of AS (4-5) were ER(-) by RT-PCR There was a significant change (pre to post) in the average Ki67 level (18% to 11%; p Pre-Tx ASER-PCR Status (Pre-Tx)NegativePositiveTotalAS 2-317 (94%)1(6%)18AS 4-59(56%)7(44%)6AS 6-70 (0%)21(100%)21Total262955 Conclusions • Results confirm earlier reports showing substantial disagreement in ER measured by IHC vs RT-PCR in patients with lower ER-expressing tumors • The clinical implications are that a substantial number of patients with low ER by IHC may have little to no benefit from HT • The 21-gene assay may be useful in selecting patients likely to benefit from HT • Further studies in larger cohorts are required to confirm these findings. Citation Format: J Michael Dixon, Arran Turnbull, Lorna Renshaw, Megan P Rothney, Cynthia A Loman, Laura Arthur, Jeremy S Thomas, Oliver Young, Juliette Murray, Linda Williams, Amy P Sing, David Cameron. Association of estrogen receptor (ER) levels and prediction of antiproliferative effect of hormone therapy (HT) in lower ER-expressing tumors [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-06-35.

Active surveillance (AS) has been widely implemented within Veterans Affairs' medical centers (VAMCs) as a standard of care for low-risk prostate cancer (PCa). Patient characteristics such as age, race, and Agent Orange (AO) exposure may influence advisability of AS in veterans. The 17-gene assay may improve risk stratification and management selection.To compare management strategies for PCa at 6 VAMCs before and after introduction of the Oncotype DX Genomic Prostate Score (GPS) assay.We reviewed records of patients diagnosed with PCa between 2013 and 2014 to identify management patterns in an untested cohort. From 2015 to 2016, these patients received GPS testing in a prospective study. Charts from 6 months post biopsy were reviewed for both cohorts to compare management received in the untested and tested cohorts.Men who just received their diagnosis and have National Comprehensive Cancer Network (NCCN) very low-, low-, and select cases of intermediate-risk PCa.Patient characteristics were generally similar in the untested and tested cohorts. AS utilization was 12% higher in the tested cohort compared with the untested cohort. In men younger than 60 years, utilization of AS in tested men was 33% higher than in untested men. AS in tested men was higher across all NCCN risk groups and races, particular in low-risk men (72% vs 90% for untested vs tested, respectively). Tested veterans exposed to AO received less AS than untested veterans. Tested nonexposed veterans received 19% more AS than untested veterans. Median GPS results did not significantly differ as a factor of race or AO exposure.Men who receive GPS testing are more likely to utilize AS within the year post diagnosis, regardless of age, race, and NCCN risk group. Median GPS was similar across racial groups and AO exposure groups, suggesting similar biology across these groups. The GPS assay may be a useful tool to refine risk assessment of PCa and increase rates of AS among clinically and biologically low-risk patients, which is in line with guideline-based care.

Objective To evaluate the new DXA VAT method on an Asian Chinese population by comparing to a reference method, computed tomography (CT). Design and Methods In total, 145 adult men and women volunteers, representing a wide range of ages (19-83 years) and BMI values (18.5-39.3 kg/m2) were studied with both DXA and CT. Results The coefficient of determination (r2) for regression of CT on DXA values was 0.947 for females, 0.891 for males and 0.915 combined. The 95% confidence interval for r was 0.940-0.969 for the combined data. The Bland–Altman test showed a VAT bias (CT as standard method) of 143 cm3 for females and 379 cm3 for males. Combined, the bias was 262 cm3 with 95% limits of agreement of −232 to 755 cm3. While the current DXA method moderately overestimates the VAT volume for the study subjects, a further analysis suggested that the overestimation could be largely contributed to VAT movement due to breath-holding status. Conclusions For Asian Chinese, VAT measured with DXA is highly correlated to VAT measured with CT. Validation of the DXA VAT tool using a reference method (e.g., CT) needs to carefully control the breath-holding protocol.

A dual-energy X-ray absorptiometry (DXA) application to measure visceral adipose tissue (VAT) in the android region of a total body DXA scan has recently been developed. This new application, CoreScan, has been validated on the Lunar iDXA (GE Healthcare, Madison, WI) densitometer against volumetric computed tomography. The geometric assumptions underlying the CoreScan model are the same on the Prodigy (GE Healthcare, Madison, WI) densitometer. However, differences between the peak X-ray voltage and detector array configurations may lead to differences in VAT quantification. The purpose of this study was to evaluate the agreement of Prodigy and iDXA CoreScan values and to characterize differences in VAT precision between the instruments. Data from volunteers with paired Prodigy and iDXA measurements were used to define empirical adjustments to the VAT algorithm parameters (n=59) and validate performance on Prodigy (n=62). Prodigy VAT measurements were highly correlated to iDXA (r=0.984). The mean of the Prodigy-iDXA VAT volume differences was -13.8cm³ with a 95% confidence interval of -45 to +17cm³. The Bland-Altman 95% limits of agreement for the 2 methods were -252 to +224cm³. Measurement of short-term precision showed that measurement error variance on iDXA was smaller (p

The purpose of this study was to validate a two-regression model for predicting energy expenditure (EE) from ActiGraph GT1M accelerometer-generated activity counts using a whole-room indirect calorimeter and the doubly labeled water (DLW) technique. We also investigated if a low-pass filter (LPF) approach would improve the model's accuracy in the minute-to-minute EE prediction.Thirty-four healthy volunteers (age = 20-67 yr, body mass index = 19.3-52.1 kg.m) spent approximately 24 h in a room calorimeter while wearing a GT1M monitor and performed structured and self-selected activities followed by overnight sleep. The EE predicted by the models and expressed in metabolic equivalents (MET-minutes) during waking times was compared with the room calorimeter-measured EE. A subset of volunteers (n = 22) completed a 14-d DLW protocol in free living while wearing an ActiGraph. The average daily EE predicted by the models (MET-minutes) was compared with the DLW.Compared with the room calorimeter, the two-regression model overpredicted EE by 10.2% +/- 11.4% (1282 +/- 125 and 1174 +/- 152 MET.min, P0.001) and time spent in moderate physical activity (PA) by 36.9 +/- 46.0 min while underestimating the time spent in light PA by -48.3 +/- 55.0 min (P0.05). The LPF reduced the squared and mean absolute error in the EE prediction (P0.05) but not the prediction error in time spent in moderate or light PA (both P0.05). The EE measured by DLW (2108 +/- 358 MET.min.d) and predicted by both filtered and unfiltered models (2104 +/- 218 and 2192 +/- 228 MET.min.d, respectively) were similar (P0.05).The two-regression model with LPF showed good agreement with total EE measured using room calorimeter and DLW. However, the individual variability in assessing time spent in sedentary, low, and moderate PA intensities and related EE remains significant.

Dual-energy X-ray absorptiometry (DXA) has become a common measurement of human body composition. However, obese subjects have been understudied largely due to weight and scan area restrictions. Newer DXA instruments allow for heavier subjects to be supported by the DXA scanner, but the imaging area is still smaller than the body size of some obese subjects. In this study, we determined the validity of an automated half-scan methodology by comparing to the standard whole-body scans in a cohort of obese volunteers. Fifty-two subjects whose BMI30 kg/m2 completed whole-body iDXA (GE Lunar) scans. The resulting scans were analyzed in three ways: the standard whole-body scan, total body estimated from the left side, and from the right side. Fat mass, nonbone lean mass, bone mineral content (BMC), and percent fat derived from each half scan were compared to the whole-body scans. Total fat mass, nonbone lean mass, or percent fat was comparable for the whole-body scans, left, and right side scans (97% within individuals and99.9% for the group). The BMC estimate using the right side scan was slightly but statistically higher than the whole-body BMC (approximately 30 g or 1%, P0.001), while the left side scan BMC estimate was lower than the whole-body BMC by the same magnitude. No significant magnitude bias was found for any of the composition variables. We conclude that the new iDXA half-body analysis in obese subjects appears to be closely comparable to whole-body analysis for fat mass, nonbone lean mass, and percent fat.

Introduction Breast cancer in young women (

Background: Abdominal visceral fat, typically measured by computer tomography (CT) or magnetic resonance imaging (MRI), has been shown to correlate with cardiometabolic risks. The purpose of this study was to examine whether a newly developed and validated visceral fat measurement from dual-energy X-ray absorptiometry (DXA) provides added predictive value to the cross-sectional differences of cardiometabolic parameters beyond the traditional anthropometric and DXA adiposity parameters. Method: A heterogeneous cohort of 194 adults (81 males and 113 females) with a BMI of 19 to 54 kg/m2 participated in this cross-sectional study. Body composition was measured with a DXA densitometer. Visceral fat was then computed with a proprietary algorithm. Insulin sensitivity index (SI, measured by intravenous glucose tolerance test), blood pressures, and lipid profiles, and peak oxygen uptake were also measured as cardiometabolic risk parameters. Results: DXA-estimated visceral fat mass was associated with HDL cholesterol (regression coefficient [β] = −5.15, P < .01, adjusted R2 = .21), triglyceride (β = 26.01, P < .01, adjusted R2 = .14), and peak oxygen uptake (β = −3.15, P < .01, adjusted R2 = .57) after adjusting for age, gender, and ethnicity. A subanalysis stratifying gender-specific BMI tertiles showed visceral fat, together with ethnicity, was independently associated with SI in overweight men and moderately obese women (second tertile). Conclusions: Without requiring additional CT or MRI-based measurements, visceral fat detected by DXA might offer certain advantages over the traditional DXA adiposity parameters as means of assessing cardiometabolic risks.

The use of palpation information for skin disease characterization is not as commonly used as in other soft tissues, although mechanical differences within lesions have been noted. For example, regions of hyperkeratosis have the potential to transform into cancerous lesions and likely feature different material properties from those of surrounding normal tissue due to varying cytoarchitecture. As a result, the spatial distribution of lesion mechanical properties may serve to assist a diagnosis or enhance visualization of the complete extent of a cancerous region, i.e., accurate information regarding the margins of disease for surgical therapy. In this work, a multiresolution extension to a novel elastographic imaging method called Modality Independent Elastography (MIE) is used to characterize the mechanical properties of a skin-like phantom embedded with a mock stiff lesion. Simulation studies were also performed to investigate the potential for characterizing realistic melanoma lesions. Elasticityimage reconstructions from the phantom experiments localized the stiff inclusion and had good correlation between the Young’s moduluscontrast ratio and experimental measurements from material testing. In addition, multiresolution MIE was shown to be a more robust framework than its single-resolution version. Results from the melanoma simulation demonstrate the potential for using multiresolution MIE with dermoscopic images.

5063 Background: A 17 gene panel (Oncotype Dx Genomic Prostate Score, GPS) has been validated as an independent predictor of adverse pathology (AP, defined as pathological GS 4+3 or higher and/or pT3+) in men treated with radical prostatectomy (RP) for prostate cancer (PCa). Multiparametric Magnetic Resonance Imaging (mpMRI) may help guide prostate biopsies. We explored synergies between GPS and mpMRI to aid in PCa management decisions. Methods: A cohort of men with NCCN Low and Intermediate-Risk PCa who were managed with RP was identified from a clinical database. Patients were required to have had a simultaneous mpMRI-guided and systematic biopsy and to have undergone RP within 6 months. Biopsy tissue of the highest Gleason pattern was used for calculation of GPS. The primary endpoint was AP. Secondary endpoints included the range of GPS within UCLA prostate MRI risk groups and median GPS when there was discrepancy between MRI and systematic biopsy Gleason Score (GS). Logistic regression models were fit to evaluate the relationship between GPS (per 20 units) and AP. Results: 134 men met criteria for the primary endpoint. Median age was 62 years (range 46-77). NCCN Low & Intermediate-Risk PCa was present in 16%, and 84% of men, respectively. Biopsy GS 3+3/3+4/4+3 was present in 19%, 67%, and 13%, respectively. In a univariable model, GPS was associated with AP (OR 3.8, 95% CI 2.1 to 7.4, p < 0.001). After adjustment for highest biopsy GS and clinical T-stage, GPS remained significantly associated with AP (OR 3.4, 95% CI 1.8 to 6.8, p = 0.0004). A wide and overlapping distribution of GPS was noted across UCLA MRI prostate risk groups, indicating that GPS provides information that is distinct from what can be determined from mpMRI. When there was a discrepancy between mpMRI and systematic biopsy GS, mpMRI targeted lesions with higher GS had higher median GPS (33, range 13-70) than systematic biopsies with higher GS (median GPS 25, range 15-55). Conclusions: GPS provides independent and complementary prognostic information to mpMRI-guided biopsies. The combination of mpMRI for biopsy guidance and GPS for molecular analysis may optimize prediction of AP and improve patient selection for treatment versus surveillance.

54 Background: Active surveillance (AS) is a recommended management approach for low risk prostate cancer (PCa). Studies have shown high rates of AS in the Veterans Administration (VA), but concerns about missing aggressive disease lead to variation between centers. The 17-gene Genomic Prostate Score (GPS) has been validated to predict likelihood of favorable pathology (LFP) in men with clinically low risk PCa. This study compared treatment patterns before and after introduction of the GPS to determine if the assay influenced treatment patterns. Methods: Men newly diagnosed with PCa who met NCCN criteria for very low (VL), low (L), or intermediate (INT) risk PCa were eligible. Chart review of men across 6 VA medical centers (VAMCs) established treatment in untested patients in 2013-2014. In 2015, Veterans at the same VAMCs were offered the assay in a prospective study measuring treatment recommendations before and after the assay and treatment implemented based on chart review. Results: There were 200 men in the untested cohort. Characteristics: age (median = 66, range:43-83), Gleason Score (GS) (3+3:64%, 3+4:37%), PSA (mean = 6.6, range:0.7-20), NCCN risk (VL:18%, L:37%, INT:46%). There were 190 men in the prospective study with complete data. NCCN risk group: age (median = 66, range:50-85), GS (3+3:74%, 3+4:26%), PSA (mean = 6.4, range:0.4-18.1), VL:22%, L:43%, INT:35%. GPS ranged from 0-61 and LFP ranged from 38%-91%. GPS identified 24 patients who had more favorable pathology and 13 patients who had less favorable pathology than would be expected using NCCN alone. 62% of untested Veterans pursued AS compared to 74% of tested Veterans. AS increases between untested and tested cohorts were 1% in VL, 16% in L, and 3% in INT. Conclusions: Both untested and tested patients had clinical characteristics representative of low risk PCa in the VA. Use of AS increased in tested Veterans compared to untested, with the largest increases observed in NCCN low risk patients. The 17-gene assay used biological information to provide refined risk estimates in tested Veterans, assisting physicians in appropriately identifying candidates for AS or immediate treatment.

Physical activity is essential to health. Accelerometry-based activity monitors are widely used in clinical and epidemiological research settings; however, only measuring body movement may prohibit accurate prediction of energy expenditure. Recent technological advancements allow synchronous measurements of heart rate, body temperature, acceleration, and other physiological responses and record them in detail (every minute or finer precision). Current multisensor devices are small, wireless, and capable of continuously recording data over several days or weeks, making them readily applicable in the free-living environment. Future studies should focus on developing strategies to optimize sensor data for accurate and robust predictions of clinically pertinent outcome parameters, such as total daily energy expenditure and physical activity energy expenditure. There is also a need for calibration instruments to allow users to standardize devices in their own laboratory or clinic. We also call for more transparency in publishing sensor properties and modeling algorithms, rather than proprietary or "black-box" prediction approaches.

Objective To examine the association between cardiometabolic risk factors and visceral adipose tissue (VAT) measurements using a dual-energy X-ray absorptiometry (DXA) based approach. Design and Methods An analysis of cross-sectional relationships between DXA VAT measured using CoreScan (GE Healthcare) and cardiometabolic indicators was conducted on a sample of 939 subjects (541 females and 398 males; average age, 56 years; average BMI, 26 kg/m2) who had previously undergone a total body DXA scan as well as measurements of key cardiometabolic risk factors. Results Sex-specific, age-adjusted multivariable regression analysis showed that for both men and women, DXA VAT was significantly associated with increased odds of hypertension, impaired fasting glucose, metabolic syndrome, and type 2 diabetes (P < 0.001). After additional model adjustment for BMI and waist circumference, the odds ratio (per SD change in VAT) for type 2 diabetes was 2.07 for women and 2.25 for men. Similarly, the odds ratio for metabolic syndrome for women was 3.46 and for men was 1.75. Conclusions VAT measured using DXA showed a significant association with cardiometabolic risk factors and disease. These relationships persist after statistical adjustment for age, BMI, and waist circumference. DXA VAT may provide a new accessible option for quantifying VAT-related cardiometabolic risk.

Objective: A new tool to quantify visceral adipose tissue (VAT) over the android region of a total body dual-energy x-ray absorptiometry (DXA) scan has recently been reported. The measurement, CoreScan, is currently available on Lunar iDXA densitometers. The purpose of the study was to determine the precision of the CoreScan VAT measurement, which is critical for understanding the utility of this measure in longitudinal trials. Design and Methods: VAT precision was characterized in both an anthropomorphic imaging phantom (measured on 10 Lunar iDXA systems) and a clinical population consisting of obese women (n = 32). Results: The intrascanner precision for the VAT phantom across 9 quantities of VAT mass (0–1,800 g) ranged from 28.4 to 38.0 g. The interscanner precision ranged from 24.7 to 38.4 g. There was no statistical dependence on the quantity of VAT for either the inter- or intrascanner precision result (p = 0.670). Combining inter- and intrascanner precision yielded a total phantom precision estimate of 47.6 g for VAT mass, which corresponds to a 4.8% coefficient of variance (CV) for a 1 kg VAT mass. Our clinical population, who completed replicate total body scans with repositioning between scans, showed a precision of 56.8 g on an average VAT mass of 1110.4 g. This corresponds to a 5.1% CV. Hence, the in vivo precision result was similar to the phantom precision result. Conclusions: The study suggests that CoreScan has a relatively low precision error in both phantoms and obese women and therefore may be a useful addition to clinical trials where interventions are targeted towards changes in visceral adiposity.

e16570Background: The overtreatment of prostate cancer and underutilization of active surveillance in men with Gleason 6 (GS6) cancer stems from uncertainty with current risk instruments such as vo...

e16611Background: Active surveillance (AS) is a recommended treatment option for low risk prostate cancer (PCa). Studies have shown high rates of AS in the Veterans Administration (VA) yet treatmen...

To evaluate the new DXA VAT method on an Asian Chinese population by comparing to a reference method, computed tomography (CT).In total, 145 adult men and women volunteers, representing a wide range of ages (19-83 years) and BMI values (18.5-39.3 kg/m(2) ) were studied with both DXA and CT.The coefficient of determination (r(2) ) for regression of CT on DXA values was 0.947 for females, 0.891 for males and 0.915 combined. The 95% confidence interval for r was 0.940-0.969 for the combined data. The Bland-Altman test showed a VAT bias (CT as standard method) of 143 cm(3) for females and 379 cm(3) for males. Combined, the bias was 262 cm(3) with 95% limits of agreement of -232 to 755 cm(3) . While the current DXA method moderately overestimates the VAT volume for the study subjects, a further analysis suggested that the overestimation could be largely contributed to VAT movement due to breath-holding status.For Asian Chinese, VAT measured with DXA is highly correlated to VAT measured with CT. Validation of the DXA VAT tool using a reference method (e.g., CT) needs to carefully control the breath-holding protocol.

Obesity is the major risk factor for metabolic syndrome and through it diabetes as well as cardiovascular disease. Visceral fat (VF) rather than subcutaneous fat (SF) is the major predictor of adverse events. Currently, the reference standard for measuring VF is abdominal X-ray computed tomography (CT) or magnetic resonance imaging (MRI), requiring highly used clinical equipment. Dual-energy X-ray absorptiometry (DXA) can accurately measure body composition with high-precision, low X-ray exposure, and short-scanning time. The purpose of this study was to validate a new fully automated method whereby abdominal VF can be measured by DXA. Furthermore, we explored the association between DXA-derived abdominal VF and several other indices for obesity: BMI, waist circumference, waist-to-hip ratio, and DXA-derived total abdominal fat (AF), and SF. We studied 124 adult men and women, aged 18-90 years, representing a wide range of BMI values (18.5-40 kg/m(2)) measured with both DXA and CT in a fasting state within a one hour interval. The coefficient of determination (r(2)) for regression of CT on DXA values was 0.959 for females, 0.949 for males, and 0.957 combined. The 95% confidence interval for r was 0.968 to 0.985 for the combined data. The 95% confidence interval for the mean of the differences between CT and DXA VF volume was -96.0 to -16.3 cm(3). Bland-Altman bias was +67 cm(3) for females and +43 cm(3) for males. The 95% limits of agreement were -339 to +472 cm(3) for females and -379 to +465 cm(3) for males. Combined, the bias was +56 cm(3) with 95% limits of agreement of -355 to +468 cm(3). The correlations between DXA-derived VF and BMI, waist circumference, waist-to-hip ratio, and DXA-derived AF and SF ranged from poor to modest. We conclude that DXA can measure abdominal VF precisely in both men and women. This simple noninvasive method with virtually no radiation can therefore be used to measure VF in individual patients and help define diabetes and cardiovascular risk.

Although the measurement of physical activity with wearable monitors may be considered objective, consensus guidelines for collecting and processing these objective data are lacking. This article presents an algorithm embodying best practice recommendations for collecting, processing, and reporting physical activity data routinely collected with accelerometry-based activity monitors. This algorithm is proposed as a linear series of seven steps within three successive phases. The Precollection Phase includes two steps. Step 1 defines the population of interest, the type and intensity of physical activity behaviors to be targeted, and the preferred outcome variables, and identifies the epoch duration. In Step 2, the activity monitor is selected, and decisions about how long and where on the body the monitor is to be worn are made. The Data Collection Phase, Step 3, consists of collecting and processing activity monitor data and is dependent on decisions made previously. The Postcollection Phase consists of four steps. Step 4 involves quality and quantity control checks of the activity monitor data. In Step 5, the raw data are transformed into physiologically meaningful units using a calibration algorithm. Step 6 involves summarizing these data according to the target behavior. In Step 7, physical activity outcome variables based on time, energy expenditure, or movement type are generated. Best practice recommendations include the full disclosure of each step within the algorithm when reporting monitor-derived physical activity outcome variables in the research literature. As such, those reading and publishing within the research literature, as well as future users, will have the best chance for understanding the interactions between study methodology and activity monitor selection, as well as the best possibility for relating their own monitor-derived physical activity outcome variables to the research literature.

Dual-energy X-ray absorptiometry (DXA) is a well-accepted technique for measuring body composition. Knowledge of measurement precision is critical for monitoring of changes in bone mineral content (BMC), and fat and lean masses. The purpose of this study was to characterize in vivo precision of total body and regional body composition parameters using the GE Lunar iDXA (GE Healthcare Lunar, Madison, WI) system in a sample of nonobese subjects. We also evaluated the difference between expert and automatic region-of-interest (ROI) analysis on body composition precision. To this end, 2 total body scans were performed on each subject with repositioning between scans. Total body precision for BMC, fat and lean mass were 0.5%, 1.0%, and 0.5% coefficient of variation (CV), respectively. Regional body composition precision error was less than 2.5% CV for all regions except arms. Precision error was higher for the arms (CV: BMC 1.5%; fat mass 2.8%; lean mass 1.6%), likely owing to the placement of arms relative to torso leading to differences in ROI. There was a significant correlation between auto ROI and expert ROI ( r >0.99). Small, but statistically significant differences were found between auto and manual ROI. Differences were small in total body, leg, trunk, and android and gynoid regions (0.004–2.8%), but larger in arm region (3.0–6.3%). Total body and regional precision for iDXA are small and it is suggested that iDXA may be useful for monitoring changes in body composition during longitudinal trials.

Whole-room indirect calorimeters are capable of measuring human metabolic rate in conditions representative of quasi-free-living state through measurement of oxygen consumption (VO(2)) and carbon dioxide production (VCO(2)). However, the relatively large room size required for patient comfort creates low signal-to-noise ratio for the VO(2) and VCO(2) signals. We proposed a wavelet-based approach to efficiently remove noise while retaining important dynamic changes in the VO(2) and VCO(2). We used correlated noise modeled from gas-infusion experiments superimposed on theoretical VO(2) sequences to test the accuracy of a wavelet based processing method. The wavelet filtering is demonstrated to improve the accuracy and sensitivity of minute-to-minute changes in VO(2), while maintaining stability during steady-state periods. The wavelet method is shown to have a lower mean absolute error and reduced total error when compared to standard methods of processing calorimeter signals.

ActiGraph accelerometers are a useful tool for objective assessment of physical activity in clinical and epidemiological studies. Several generations of ActiGraph are being used; however, little work has been done to verify that measurements are consistent across generations. This study employed mechanical oscillations to characterize the dynamic response and intermonitor variability of three generations of ActiGraph monitors, from the oldest 7164 ( n = 13), 71256 ( n = 12), to the newest GT1M ( n = 12). The response due to independent radius (22.1–60.4 mm) and frequency (25–250 rpm) changes were measured, as well as intermonitor variability within each generation. The 7164 and 71256 have similar relationships between activity counts and radius ( P = 0.229) but were significantly different from the GT1M ( P < 0.001). The frequency responses were nonlinear in all three generations. Although the response curve shapes were similar, the differences between generations at various frequencies were significant ( P < 0.017), especially in the extremes of the measurement range. Intermonitor variability was markedly reduced in the GT1M compared with the 7164 and 71256. Other measurement differences between generations include decreased peak counts and decreased sensitivity in low-frequency detection in the GT1M. The results of this study revealed an improvement of the intermonitor variability by the GT1M monitor. However, the reduced sensitivity in low-count ranges in the GT1M may not be well suited for monitoring sedentary or light-intensity movements. Furthermore, the algorithms for energy expenditure predictions developed using older 7164 monitors may need to be modified for the GT1M.

Accelerometers are promising tools for characterizing physical activity (PA) patterns in free-living persons. To date, validation of energy expenditure (EE) predictions from accelerometers has been restricted to short laboratory or simulated free-living protocols. This study seeks to determine the capabilities of eight previously published regression equations for three commercially available accelerometers to predict summary measures of daily EE.Study participants were outfitted with ActiGraph, Actical, and RT3 accelerometers, while measurements were simultaneously made during overnight stays in a room calorimeter, which provided minute-by-minute EE measurements, in a diverse subject population (n = 85). Regression equations for each device were used to predict the minute-by-minute metabolic equivalents (METs) along with the daily PA level (PAL).Two RT3 regressions and one ActiGraph regression were not significantly different from calorimeter measured PAL. When data from the entire visit were divided into four intensity categories-sedentary, light, moderate, and vigorous-significant (P0.001) over- and underpredictions were detected in numerous regression equations and intensity categories.Most EE prediction equations showed differences of2% in the moderate and vigorous intensity categories. These differences, though small in magnitude, may limit the ability of these regressions to accurately characterize whether specific PA goals have been met in the field setting. New regression equations should be developed if more accurate prediction of the daily PAL or higher precision in determining the time spent in specific PA intensity categories is desired.

e16124 Background: The 17-gene prostate cancer assay is clinically validated as a biopsy-based gene expression assay that, combined with clinical features, provides an estimate of PCa disease aggre...

101 Background: A 17-gene biopsy-based RT-PCR assay (Oncotype DX Prostate Assay) has been validated as a predictor of adverse pathology and biochemical recurrence (BCR) in clinically very low to intermediate-risk prostate cancer patients. The assay measures expression of 12 cancer and 5 reference genes that are combined to calculate a Genomic Prostate Score (GPS; scaled 0-100), providing a biologic measure of tumor aggressiveness. The cancer genes represent four biological pathways: androgen signaling, stromal response, cellular organization and proliferation. We examined the effects of variation in quantitative expression of individual gene groups on GPS results and prediction of clinical risk. Methods: The first 3,500 tumor specimens processed in the Genomic Health Inc.’s reference laboratory were included. Expression of individual genes was measured and expression of the four gene groups and GPS calculated. For each gene group, GPS of patients with the lowest 5% expression levels were contrasted with GPS of patients with highest 5% expression levels. Results: Percentages of NCCN very low, low and intermediate patients were 28%, 37%, 30%; median age was 65. Mean and median GPS were 24.6 (SD 12.0) and 23 (range 0-90). Individual gene groups exhibited wide expression ranges (e.g. proliferation-16-fold difference (FD) vs. cellular organization > 8000 FD). Large differences in expression of each gene group were reflected in GPS values and, based on a prior clinical validation study, translate into large differences in BCR risk (Table). Conclusions: Each of the four gene groups show large variations in expression, meaningfully affect the GPS, and contribute to the prediction of PCa aggressiveness. [Table: see text]

The use of palpation information for skin disease characterization is not as commonly used as in other soft tissues, although mechanical differences within lesions have been noted. For example, regions of hyperkeratosis have the potential to transform into cancerous lesions and likely feature different material properties from those of surrounding normal tissue due to varying cytoarchitecture. As a result, the spatial distribution of lesion mechanical properties may serve to assist a diagnosis or enhance visualization of the complete extent of a cancerous region, i.e., accurate information regarding the margins of disease for surgical therapy. In this work, a multiresolution extension to a novel elastographic imaging method called Modality Independent Elastography (MIE) is used to characterize the mechanical properties of a skin-like phantom embedded with a mock stiff lesion. Simulation studies were also performed to investigate the potential for characterizing realistic melanoma lesions. Elasticity image reconstructions from the phantom experiments localized the stiff inclusion and had good correlation between the Young's modulus contrast ratio and experimental measurements from material testing. In addition, multiresolution MIE was shown to be a more robust framework than its single-resolution version. Results from the melanoma simulation demonstrate the potential for using multiresolution MIE with dermoscopic images.

This study uses a similarity-based elastography method to attempt to reconstruct elastic modulus values in a simulation of cancerous tumors in the breast. Four similarity metrics were compared as to their ability to resolve a single near field tumor, far field tumor and a multiple tumor scenario. Mutual information provided the best reconstruction for near field tumors while gradient correlation provided the best reconstruction for the far field and multiple tumor models. In all elasticity images, good tumor localization was achieved; however, the limited contrast resolution needs further investigation.

33 Background: Tumor size is a clinicopathologic factor often used in early stage breast cancer (EBC) management to estimate prognosis and make decisions about therapy. While in general, small tumors have a lower chance of recurring than large tumors, some patients with small tumors have poor outcomes. The 21-gene breast cancer assay (OncotypeDX) yields a Recurrence Score result that predicts the 10-yr risk of distant recurrence (DR) and the likelihood of chemotherapy (CT) benefit in patients (pts) with ER+ EBC. This study reviews the clinical evidence and experience of the 21-gene assay in subcentimeter (subCM) tumors and shows that the Recurrence Score is more reflective of the underlying tumor biology. Methods: A meta-analysis of Genomic Health validation and supportive studies reporting Recurrence Score result and tumor size was conducted in order to describe the distribution of Recurrence Score results. Results: There were 10 GHI-sponsored studies (7,094 pts) that presented Recurrence Score results as a function of tumor size. The studies varied in the recorded tumor sizes, ranging from < = 0.5 cm to > 5 cm. Four studies specifically examined the distribution of Recurrence Score results in subCM tumors and identified a total of 629 pts out of 2,912 pts (21.6%) that fit the size criteria of < 1cm. A broad distribution of score results was observed in subCM tumors in the four studies combined: 61% low, 25% int, 15% high. Conclusions: These results demonstrate that not all pts with subCM tumors have low risk disease, and that the 21-gene assay can help inform the risk of DR more precisely as well as predict the likelihood of CT benefit. Approximately 40% of pts had intermediate or high score results, suggesting an increased potential for DR and CT benefit. The clinical implications of this meta-analysis are that size doesn’t tell the whole story. There is underlying biology reflected in the Recurrence Score that can better inform the treatment decision for pts with ER+ EBC. [Table: see text]

11003 Background: The Oncotype DX 21-gene Recurrence Score assay was developed in endocrine-treated patients (pts) and validated as a predictor of 10-yr distant recurrence risk and chemotherapy ben...

to the editor: We truly appreciate the attention paid to our work by Brage et al. ([2][1]). Although we feel that these authors made several valid points in their letter, we welcome the opportunity to justify our choices. We thank Brage et al. for uncovering an error that was made in our

Traditional immunohistochemistry serves as a vital diagnostic assay as it allows for semiquantitatively probing the magnitude and spatial distribution of protein expression and posttranslational modifications. Unfortunately, an accurate portrayal of disease often requires several immunohistochemical stains, which are run on separate tissue sections. The application of transcriptomics analyses in cancer classification has led to the generation of multivariate index analyses that confer diagnostic, prognostic, and predictive signatures of disease. However this method is limited by the inability consider target expression in the context of tissue (stroma, epithelium) or cell (e.g. stem/progenitor cells) type. A unifying platform that would allow for the quantitative spatial analysis of multiplexed in situ target measurements promises to exploit the best features of both systems. To this end, we have developed a novel multiplexed fluorescence immunohistochemistry assay that is capable of quantitative analysis of >25 antigens in a single formalin-fixed paraffin-embedded tissue section, as well as image and data analysis capabilities for analyzing the multidimensional data. By inclusion of targets for cell and tissue compartments, including nuclei, cytoplasm and membrane, we have demonstrated the ability to investigate subcellular protein expression, phosphorylation and co-localization in individual cells. In the present study we have stained a cohort of 79 prostate cancer patients of varying Gleason grades for a total of 24 antigens, representing key mediators of cell signaling, tumor suppressors and oncogenes, tumor associated phenotypic targets, and structural proteins. The images are precisely registered and segmented into individual cells nuclear, cytoplasmic and membrane regions and the underlying expression of a given antigen is then quantitatively determined in each compartment by automated algorithms. With the advent of this new tool, we aim to define new prognostic molecular signatures in prostate cancer. Citation Information: Clin Cancer Res 2010;16(14 Suppl):A28.

Visceral adiposity is increasingly recognized as a key condition for the development of obesity related disorders, with the ratio between visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) reported as the best correlate of cardiometabolic risk. In this study, using a cohort of 40 obese females (age: 25-45 y, BMI: 28-40 kg/m(2)) under healthy clinical conditions and monitored over a 2 weeks period we examined the relationships between different body composition parameters, estimates of visceral adiposity and blood/urine metabolic profiles. Metabonomics and lipidomics analysis of blood plasma and urine were employed in combination with in vivo quantitation of body composition and abdominal fat distribution using iDXA and computerized tomography. Of the various visceral fat estimates, VAT/SAT and VAT/total abdominal fat ratios exhibited significant associations with regio-specific body lean and fat composition. The integration of these visceral fat estimates with metabolic profiles of blood and urine described a distinct amino acid, diacyl and ether phospholipid phenotype in women with higher visceral fat. Metabolites important in predicting visceral fat adiposity as assessed by Random forest analysis highlighted 7 most robust markers, including tyrosine, glutamine, PC-O 44∶6, PC-O 44∶4, PC-O 42∶4, PC-O 40∶4, and PC-O 40∶3 lipid species. Unexpectedly, the visceral fat associated inflammatory profiles were shown to be highly influenced by inter-days and between-subject variations. Nevertheless, the visceral fat associated amino acid and lipid signature is proposed to be further validated for future patient stratification and cardiometabolic health diagnostics.