Ovarian Cancer surgical consideration is markedly improved by the neural network powered-MIA3G multivariate index assay.

Background: Surgery remains the main treatment option for an adnexal mass suspicious of ovarian cancer. The malignancy rate is, however, only 10-15% in women undergoing surgery. This results in a high number of unnecessary surgeries. A surveillance-based approach is recommended to form the basis for surgical referrals. We have previously reported the clinical performance of MIA3G, a deep neural network-based algorithm, for assessing ovarian cancer risk. In this study, we show that MIA3G markedly improves the surgical selection for women presenting with adnexal masses. Methods: MIA3G employs seven serum biomarkers, patient age, and menopausal status. Serum samples were collected from 785 women (IQR: 39-55 years) across 12 centers that presented with adnexal masses. MIA3G risk scores were calculated for all subjects in this cohort. Physicians had no access to the MIA3G risk score when deciding upon a surgical referral. The performance of MIA3G for surgery referral was compared to clinical and surgical outcomes. MIA3G was also tested in an independent cohort comprising 29 women across 14 study sites, in which the physicians had access to and utilized MIA3G prior to surgical consideration. Results: When compared to the actual number of surgeries (n = 207), referrals based on the MIA3G score would have reduced surgeries by 62% (n = 79). The reduction was higher in premenopausal patients (77%) and in patients ≤55 years old (70%). In addition, a 431% improvement in malignancy prediction would have been observed if physicians had utilized MIA3G scores for surgery selection. The accuracy of MIA3G referral was 90.00% (CI 87.89-92.11), while only 9.18% accuracy was observed when the MIA3G score was not used. These results were corroborated in an independent multi-site study of 29 patients in which the physicians utilized MIA3G in surgical consideration. The surgery reduction was 87% in this cohort. Moreover, the accuracy and concordance of MIA3G in this independent cohort were each 96.55%. Conclusion: These findings demonstrate that MIA3G markedly augments the physician's decisions for surgical intervention and improves malignancy prediction in women presenting with adnexal masses. MIA3G utilization as a clinical diagnostic tool might help reduce unnecessary surgeries.

Neural network-derived multivariate index assay demonstrates effective clinical performance in longitudinal monitoring of ovarian cancer risk.

OBJECTIVE: We recently characterized the clinical performance of a multivariate index assay (MIA3G) to assess ovarian cancer risk for adnexal masses at initial presentation. This study evaluated how MIA3G varies when applied longitudinally to monitor risk during clinical follow-up. METHOD: The study evaluated women presenting with adnexal masses from eleven centers across the US. Patients received an initial blood draw at enrollment and at the standard-of-care follow-up visits. MIA3G was determined for all visits but physicians did not have access to MIA3G scores to determine clinical management. The primary outcome was the relative change value (RCV) of MIA3G over the period of clinical observation. RESULTS: A total of 510 patients of 785 enrolled met study criteria. Of these, 30.8% had a second, 25.4% a third and 22.2% a fourth blood draw following initial collection. The median duration from initial draw was 131 d to second draw, 301.5 d to the third draw and 365.5 d to the fourth draw. MIA3G RCV of >50% was observed in 22-26% patients, whereas 70-75% patients had MIA3G RCV >5%. An empirical baseline RCV of 56% - transformed to 1 in logarithmic scale - was calculated from averaging RCVs of all patients who had no malignancy risk after 210 days. RCV > 1 log was associated with higher incidence of surgical intervention (29.6%) compared to RCV < 1 log (16.9%). CONCLUSIONS: Variation in MI3AG does not change the accuracy of the test for excluding malignancy, while marked changes may be associated with a slightly higher likelihood of surgical intervention. In addition to MIA3G score itself, the MIA3G RCV may be important for clinical management.

Validation of a deep neural network-based algorithm supporting clinical management of adnexal mass.

Background: Conservative management of adnexal mass is warranted when there is imaging-based and clinical evidence of benign characteristics. Malignancy risk is, however, a concern due to the mortality rate of ovarian cancer. Malignancy occurs in 10-15% of adnexal masses that go to surgery, whereas the rate of malignancy is much lower in masses clinically characterized as benign or indeterminate. Additional diagnostic tests could assist conservative management of these patients. Here we report the clinical validation of OvaWatch, a multivariate index assay, with real-world evidence of performance that supports conservative management of adnexal masses. Methods: OvaWatch utilizes a previously characterized neural network-based algorithm combining serum biomarkers and clinical covariates and was used to examine malignancy risk in prospective and retrospective samples of patients with an adnexal mass. Retrospective data sets were assembled from previous studies using patients who had adnexal mass and were scheduled for surgery. The prospective study was a multi-center trial of women with adnexal mass as identified on clinical examination and indeterminate or asymptomatic by imaging. The performance to detect ovarian malignancy was evaluated at a previously validated score threshold. Results: In retrospective, low prevalence (N = 1,453, 1.5% malignancy rate) data from patients that received an independent physician assessment of benign, OvaWatch has a sensitivity of 81.8% [95% confidence interval (CI) 65.1-92.7] for identifying a histologically confirmed malignancy, and a negative predictive value (NPV) of 99.7%. OvaWatch identified 18/22 malignancies missed by physician assessment. A prospective data set had 501 patients where 106 patients with adnexal mass went for surgery. The prevalence was 2% (10 malignancies). The sensitivity of OvaWatch for malignancy was 40% (95% CI: 16.8-68.7%), and the specificity was 87% (95% CI: 83.7-89.7) when patients were included in the analysis who did not go to surgery and were evaluated as benign. The NPV remained 98.6% (95% CI: 97.0-99.4%). An independent analysis set with a high prevalence (45.8%) the NPV value was 87.8% (95% CI: 95% CI: 75.8-94.3%). Conclusion: OvaWatch demonstrated high NPV across diverse data sets and promises utility as an effective diagnostic test supporting management of suspected benign or indeterminate mass to safely decrease or delay unnecessary surgeries.

A reflex testing protocol using two multivariate index assays improves the risk assessment for ovarian cancer in patients with an adnexal mass.

OBJECTIVES: Patients with adnexal masses suspicious for malignancy benefit from referral to oncology specialists during presurgical assessment of the mass. OVA1 is a multivariate assay using a five-biomarker panel which offers high overall and early-stage sensitivity. However, OVA1 has a high false-positive rate for benign masses. Overa, a second-generation multivariate index assay was developed to reduce the false-positive rate. The aim of the present study was to use Overa as a reflex for OVA1 and increase specificity. METHODS: OVA1 cut-off scores were established to place patients into three categories: low, intermediate, and high cancer risk. Samples with intermediate-risk OVA1 scores were reflexed to the Overa and defined as high or low risk. This protocol was tested with 1035 prospectively collected serum samples and validated with an independent prospectively collected sample set (N = 207). RESULTS: Thirty-five per cent (359) of samples had intermediate OVA1 scores. Reflexing these to Overa eliminated 58% of the false-positives and improved the overall specificity from 50% to 72%. This finding was confirmed in the independent dataset, in which the specificity increased from 56% to 73%. CONCLUSIONS: Reflexing samples with intermediate OVA1 scores significantly decreases the false-positive rate, thereby reducing unnecessary surgical referrals.

Analytical Validation of a Deep Neural Network Algorithm for the Detection of Ovarian Cancer.

PURPOSE: Early detection of ovarian cancer, the deadliest gynecologic cancer, is crucial for reducing mortality. Current noninvasive risk assessment measures include protein biomarkers in combination with other clinical factors, which vary in their accuracy. Machine learning can be applied to optimizing the combination of these features, leading to more accurate assessment of malignancy. However, the low prevalence of the disease can make rigorous validation of these tests challenging and can result in unbalanced performance. METHODS: MIA3G is a deep feedforward neural network for ovarian cancer risk assessment, using seven protein biomarkers along with age and menopausal status as input features. The algorithm was developed on a heterogenous data set of 1,067 serum specimens from women with adnexal masses (prevalence = 31.8%). It was subsequently validated on a cohort almost twice that size (N = 2,000). RESULTS: In the analytical validation data set (prevalence = 4.9%), MIA3G demonstrated a sensitivity of 89.8% and a specificity of 84.02%. The positive predictive value was 22.45%, and the negative predictive value was 99.38%. When stratified by cancer type and stage, MIA3G achieved sensitivities of 94.94% for epithelial ovarian cancer, 76.92% for early-stage cancer, and 98.04% for late-stage cancer. CONCLUSION: The balanced performance of MIA3G leads to a high sensitivity and high specificity, a combination that may be clinically useful for providers in evaluating the appropriate management strategy for their patients. Limitations of this work include the largely retrospective nature of the data set and the unequal, albeit random, assignment of histologic subtypes between the training and validation data sets. Future directions may include the addition of new biomarkers or other modalities to strengthen the performance of the algorithm.

Survey of canine use and safety of isoxazoline parasiticides.

A veterinarian and pet owner survey (Project Jake) examined the use and safety of isoxazoline parasiticides given to dogs. Data were received during August 1-31, 2018 from a total of 2,751 survey responses. Forty-two percent (1,157) reported no flea treatment or adverse events (AE), while 58% (1594) had been treated with some parasiticide for flea control, and of those that received a parasiticide, the majority, or 83% (1,325), received an isooxazoline. When any flea treatment was given, AE were reported for 66.6% of respondents, with no apparent AE noted for 36.1%. Project Jake findings were compared to a retrospective analysis of publicly available Food and Drug Administration (FDA) and European Medicines Agency (EMA) reported AE. The number of total AE reported to FDA and EMA were comparable, although a 7 to 10 times higher occurrence of death and seizures was reported from the EMA or from outside the United States (US). Serious AE responses for death, seizures and neurological effects reported in our survey were higher than the FDA but moderately lower than the EMA reports. These sizable global data sets combined with this pre- and post-parasiticide administration survey indicated that isoxazoline neurotoxicity was not flea- and tick-specific. Post-marketing serious AE were much higher than in Investigational New Drug (IND) submissions. Although the labels have recently been updated, dogs, cats and their caregivers remain impacted by their use. These aggregate data reports support the need for continued cross-species studies and critical review of product labelling by regulatory agencies and manufacturers.

Adnexal mass risk assessment: a multivariate index assay for malignancy risk stratification.

Aims: Adnexal mass risk assessment (AMRA) stratifies patients with adnexal masses, identifying the relatively small number of malignancies from benigns which might take a 'watchful waiting' approach. Methods: AMRA uses seven biomarkers and derived from women with adnexal masses scheduled for surgery. Estimated clinical performance was calculated using fixed prevalence. Results: At 5% prevalence, the high-risk group, 7.9% total, captured 75.9% of invasive malignancies at a positive predictive value of 35.8%. High risk/intermediate risk combined had a sensitivity of 89.7 and 95.6% for pre- and post-menopausal cancers, respectively. The low-risk group, 67.8% total, had an negative predictive value of 99.0%. Conclusion: With highly differentiating risk stratification capability across histological subtypes and stages, AMRA is potentially applicable to patients with adnexal masses to assist deciding whether immediate surgery is recommended.

Ethnic disparity in clinical performance between multivariate index assay and CA125 in detection of ovarian malignancy.

Aim: Based on evidence that African-American (AA) women have lower CA125 values than Caucasian (C) women, we investigated this to see if this disparity would have an impact on ovarian cancer detection using CA125 and multivariate index assay (MIA). Materials & methods: Serum from two prospective trials of 1029 (274 malignancies [250 C/24AA]) were analyzed for CA125 and MIA results. Clinical performance was calculated. Results: Sensitivity of MIA in Caucasian women was 93.2%, 74.4% for CA125 at the ACOG approved cut-off level of 200 U/ml cutoff, and 80.4% using the 2007, Dearking 67 U/ml cutoff. In AA American women, MIA sensitivity was 79.2%, 33.3% for CA125 at the ACOG approved cut-off levels and 62.5% at the 2007, Dearking 67 U/ml cutoff. Conclusion: Our results support that CA125 in AA women with adnexal masses has lower sensitivity than MIA no matter what the cutoff value is. Implementation of MIA in evaluation of adnexal masses should increase sensitivity of detection of malignancy compared with CA125, particularly in AA women.

Multivariate Index Assay Is Superior to CA125 and HE4 Testing in Detection of Ovarian Malignancy in African-American Women.

OBJECTIVE: To review and analyze the serum values of risk of ovarian malignancy algorithm (ROMA) and multivariate index assay (MIA) in subgroups of women who underwent surgery for adnexal masses to determine sensitivity, specificity, and positive and negative predictive values for the detection of malignancy in different ethnic populations. METHODS: Serum samples from 2 prospective trials of 1029 women in which 274 women diagnosed with malignancy were analyzed for ROMA scores and MIA results. Biomarker data were obtained from the previous prospective studies that validated the MIA test. Of these, 250 women were Caucasian (C) and 24 were African-American (AA). Sensitivity, specificity, positive and negative predictive values, and confidence intervals for preoperative test results were calculated using DTComPair package of the R programming language. In premenopausal women, a ROMA value equal to or greater than 1.14 indicates a high risk of finding epithelial ovarian cancer. In premenopausal women, MIA values greater than 5.0 are associated with a greater risk of malignancy. In postmenopausal women, a ROMA value equal to or greater than 2.99 indicates a high risk of finding epithelial ovarian cancer. In postmenopausal women, MIA values greater than 4.4 are associated with a greater risk of malignancy. RESULTS: Primary ovarian malignancy was diagnosed in 179 cases (167 C/12 AA) and metastatic disease to the ovary in an additional 27 cases (22 C/5 AA). Overall results are shown below. CONCLUSIONS: Our results demonstrate that ROMA in AA women with adnexal masses have lower sensitivity for the detection of malignancy than does MIA. Implementation of MIA in the evaluation of adnexal masses will increase the sensitivity of the detection of malignancy compared with ROMA, with the most marked results in AA women.

Detection and Prognostic Significance of Circulating Tumor Cells in Patients With Metastatic Thyroid Cancer.

CONTEXT: Individual patient prognostication for advanced thyroid cancer (TC) is challenging. Circulating tumor cells (CTCs) have been shown to be a valuable prognostic marker for other solid cancers. OBJECTIVE: We hypothesized that CTCs are present in the blood of patients with advanced TC and their number can predict overall survival (OS). SETTING: This is a prospective study at a tertiary cancer hospital. Patients, Interventions, and Main Outcome Measures: Initial studies were performed with TC cell lines to determine the feasibility of detection using the Veridex CellSearch. CTC enumeration was performed in blood samples from 18 patients with distantly metastatic medullary TC (metMTC), 14 with distantly metastatic differentiated TC (metDTC), and 10 controls with a history of TC but no evidence of disease. The prognostic value of CTC levels to predict OS in metMTC patients was assessed. RESULTS: CellSearch detected cells from MTC and DTC but not anaplastic TC cell lines. Six metMTC patients but no metDTC or control patients had more than or equal to 5 CTCs detected by the CellSearch assay. Median survival in metMTC patients with more than or equal to 5 CTCs was 13 months vs 51.5 months for those with less than 5 CTCs (P = .0116). The hazard ratio for mortality of patients with more than or equal to 5 CTCs compared with those with less than 5 CTCs was 3.95 (1.20-13.0, P = .0245). CONCLUSIONS: The presence of more than or equal to 5 CTCs in patients with metMTC is associated with worse OS. Larger cohorts are required to validate the prognostic value of CTC enumeration.

Predicting Prostate Biopsy Results Using a Panel of Plasma and Urine Biomarkers Combined in a Scoring System.

BACKGROUND: Determining the need for prostate biopsy is frequently difficult and more objective criteria are needed to predict the presence of high grade prostate cancer (PCa). To reduce the rate of unnecessary biopsies, we explored the potential of using biomarkers in urine and plasma to develop a scoring system to predict prostate biopsy results and the presence of high grade PCa. METHODS: Urine and plasma specimens were collected from 319 patients recommended for prostate biopsies. We measured the gene expression levels of UAP1, PDLIM5, IMPDH2, HSPD1, PCA3, PSA, TMPRSS2, ERG, GAPDH, B2M, AR, and PTEN in plasma and urine. Patient age, serum prostate-specific antigen (sPSA) level, and biomarkers data were used to develop two independent algorithms, one for predicting the presence of PCa and the other for predicting high-grade PCa (Gleason score [GS] ≥7). RESULTS: Using training and validation data sets, a model for predicting the outcome of PCa biopsy was developed with an area under receiver operating characteristic curve (AUROC) of 0.87. The positive and negative predictive values (PPV and NPV) were 87% and 63%, respectively. We then developed a second algorithm to identify patients with high-grade PCa (GS ≥7). This algorithm's AUROC was 0.80, and had a PPV and NPV of 56% and 77%, respectively. Patients who demonstrated concordant results using both algorithms showed a sensitivity of 84% and specificity of 93% for predicting high-grade aggressive PCa. Thus, the use of both algorithms resulted in a PPV of 90% and NPV of 89% for predicting high-grade PCa with toleration of some low-grade PCa (GS <7) being detected. CONCLUSIONS: This model of a biomarker panel with algorithmic interpretation can be used as a "liquid biopsy" to reduce the need for unnecessary tissue biopsies, and help to guide appropriate treatment decisions.

CA11-19: a tumor marker for the detection of colorectal cancer.

BACKGROUND AND AIM: Colorectal cancer (CRC) remains the second most frequent cause of cancer deaths in the United States. Blood tests using tumor-related antigens aid in diagnosing CRC. However, higher sensitivity and specificity are needed before an acceptable tumor antigen blood test for CRC is clinically useful. This study describes the diagnostic accuracy of an enzyme-linked immunosorbent assay for the CA11-19 serologic tumor antigen for the detection of CRC. METHODS: Serum specimens were obtained from 522 colonoscopy-confirmed subjects in institutional review board-approved studies. Specimens were blind coded. CA11-19 levels were determined by using enzyme-linked immunosorbent assay analysis. The results were tabulated for categories of normal, hyperplastic polyps, benign GI, adenomatous polyps, and CRC based on their final diagnosis. RESULTS: When a cutoff of 6.4 units/mL for normal is used, the CA11-19 level was elevated in 128 of 131 of CRC subjects, for an observed sensitivity of 98% (95% confidence interval, 93.1%-99.5%). Normal levels were found in 87% of normal subjects (90/103) and 83% of those with benign GI diseases (185/223). When combined, this yields an observed specificity of 84% (95% confidence interval, 80.0%-87.9%). CONCLUSION: CA11-19 is a serologic tumor marker for the diagnosis of CRC with a sensitivity of 98% and specificity of 84%. This high sensitivity means that this test will detect 43 of 44 cases of CRC presented. For those older than 50 years of age, it has a positive predictive value of 3.6% and a negative predictive value of 99.98%. Additional prospective studies are needed to further clarify the use of CA11-19 as an aid in the diagnosis of CRC.

Diagnostic and prognostic scoring system for prostate cancer using urine and plasma biomarkers.

AIMS: To avoid relying solely on serum prostate-specific antigen (sPSA) in screening for prostate cancer (PCa), we developed a scoring system for detecting PCa and the prediction of aggressiveness. We analyzed urine and plasma specimens from 121 patients with PCa or benign prostatic hyperplasia (BPH) for the levels of UAP1, PDLIM5, IMPDH2, HSPD1, PCA3, PSA, TMPRSS2, ERG, GAPDH, and B2M genes. Patient age, sPSA level, and polymerase chain reaction data were entered through multiple algorithms to determine models most useful for the detection of cancer and predicting aggressiveness. RESULTS: In the first algorithm, we distinguished PCa from BPH (area under the receiver operating characteristic curve [AUROC] of 0.78). Another algorithm distinguished patients with the Gleason score (GS) of ≥7 from GS of <7 cancer or BPH (AUROC of 0.88). By incorporating the two algorithms into a scoring system, 75% of the analyzed samples showed concordance between the two models (99% specificity and 68% sensitivity for predicting GS ≥7 in this group). CONCLUSION: A scoring system incorporating two algorithms using urine and plasma biomarkers highly predicts the presence of GS ≥7 PCa in 75% of patients. Our algorithms may assist with both biopsy indication and patient prognosis.

A 2-stage ovarian cancer screening strategy using the Risk of Ovarian Cancer Algorithm (ROCA) identifies early-stage incident cancers and demonstrates high positive predictive value.

BACKGROUND: A 2-stage ovarian cancer screening strategy was evaluated that incorporates change of carbohydrate antigen 125 (CA125) levels over time and age to estimate risk of ovarian cancer. Women with high-risk scores were referred for transvaginal ultrasound (TVS). METHODS: A single-arm, prospective study of postmenopausal women was conducted. Participants underwent an annual CA125 blood test. Based on the Risk of Ovarian Cancer Algorithm (ROCA) result, women were triaged to next annual CA125 test (low risk), repeat CA125 test in 3 months (intermediate risk), or TVS and referral to a gynecologic oncologist (high risk). RESULTS: A total of 4051 women participated over 11 years. The average annual rate of referral to a CA125 test in 3 months was 5.8%, and the average annual referral rate to TVS and review by a gynecologic oncologist was 0.9%. Ten women underwent surgery on the basis of TVS, with 4 invasive ovarian cancers (1 with stage IA disease, 2 with stage IC disease, and 1 with stage IIB disease), 2 ovarian tumors of low malignant potential (both stage IA), 1 endometrial cancer (stage I), and 3 benign ovarian tumors, providing a positive predictive value of 40% (95% confidence interval = 12.2%, 73.8%) for detecting invasive ovarian cancer. The specificity was 99.9% (95% confidence interval = 99.7%, 100%). All 4 women with invasive ovarian cancer were enrolled in the study for at least 3 years with low-risk annual CA125 test values prior to rising CA125 levels. CONCLUSIONS: ROCA followed by TVS demonstrated excellent specificity and positive predictive value in a population of US women at average risk for ovarian cancer.

High serum thymidine kinase 1 level predicts poorer survival in patients with chronic lymphocytic leukemia.

Serum thymidine kinase 1 (TK1) levels have been reported to have prognostic significance in patients with chronic lymphocytic leukemia (CLL). Until recently, serum TK1 levels were assessed using inconvenient radioenzyme assays. In this study, we used a novel chemiluminescence assay to assess serum TK1 levels in patients with CLL at the time of first examination. We show that high serum TK1 levels predict poorer overall survival and correlate with unmutated immunoglobulin variable region genes, CD38 and ZAP-70 expression, and subsequent risk of developing large B-cell lymphoma (Richter syndrome). Similar findings were observed in a subset of patients treated with current fludarabine-based chemotherapy regimens. We suggest that serum TK1 levels analyzed using this convenient chemiluminescence assay may be useful in the risk assessment of patients with CLL.

National Academy of Clinical Biochemistry Laboratory Medicine Practice Guidelines for use of tumor markers in liver, bladder, cervical, and gastric cancers.

BACKGROUND: Updated National Academy of Clinical Biochemistry Laboratory Medicine Practice Guidelines for the use of tumor markers in the clinic have been developed. METHODS: Published reports relevant to use of tumor markers for 4 cancer sites--liver, bladder, cervical, and gastric--were critically reviewed. RESULTS: Alpha-fetoprotein (AFP) may be used in conjunction with abdominal ultrasound for early detection of hepatocellular carcinoma (HCC) in patients with chronic hepatitis or cirrhosis associated with hepatitis B or C virus infection. AFP concentrations >200 microg/L in cirrhotic patients with typical hypervascular lesions >2 cm in size are consistent with HCC. After a diagnosis of HCC, posttreatment monitoring with AFP is recommended as an adjunct to imaging, especially in the absence of measurable disease. Although several urine markers have been proposed for bladder cancer, none at present can replace routine cystoscopy and cytology in the management of patients with this malignancy. Some may, however, be used as complementary adjuncts to direct more effective use of clinical procedures. Although carcinoembryonic antigen and CA 19-9 have been proposed for use gastric cancer and squamous cell carcinoma antigen for use in cervical cancer, none of these markers can currently be recommended for routine clinical use. CONCLUSIONS: Implementation of these recommendations should encourage optimal use of tumor markers for patients with liver, bladder, cervical, or gastric cancers.

Circulating tumor cells and [18F]fluorodeoxyglucose positron emission tomography/computed tomography for outcome prediction in metastatic breast cancer.

PURPOSE: Circulating tumor cells (CTCs) and [(18)F]fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) are two new promising tools for therapeutic monitoring. In this study, we compared the prognostic value of CTC and FDG-PET/CT monitoring during systemic therapy for metastatic breast cancer (MBC). PATIENTS AND METHODS: A retrospective analyses of 115 MBC patients who started a new line of therapy and who had CTC counts and FDG-PET/CT scans performed at baseline and at 9 to 12 weeks during therapy (midtherapy) was performed. Patients were categorized according to midtherapy CTC counts as favorable (ie, < five CTCs/7.5 mL blood) or unfavorable (> or = five CTCs/7.5 mL blood) outcomes. CTC counts and FDG-PET/CT response at midtherapy were compared, and univariate and multivariate analyses were performed to identify factors associated with survival. RESULTS: In 102 evaluable patients, the median overall survival time was 14 months (range, 1 to > 41 months). Midtherapy CTC levels correlated with FDG-PET/CT response in 68 (67%) of 102 evaluable patients. In univariate analysis, midtherapy CTC counts and FDG-PET/CT response predicted overall survival (P < .001 and P = .001, respectively). FDG-PET/CT predicted overall survival (P = .0086) in 31 (91%) of 34 discordant patients who had fewer than five CTCs at midtherapy. Only midtherapy CTC levels remained significant in a multivariate analysis (P = .004). CONCLUSION: Detection of five or more CTCs during therapeutic monitoring can accurately predict prognosis in MBC beyond metabolic response. FDG-PET/CT deserves a role in patients who have fewer than five CTCs at midtherapy. Prospective trials should evaluate the most sensitive and cost-effective modality for therapeutic monitoring in MBC.

Circulating tumor cells in metastatic breast cancer: from prognostic stratification to modification of the staging system?

BACKGROUND: The aim of the current study was to assess the prognostic value of baseline circulating tumor cells (CTCs) in a large cohort of patients with newly diagnosed metastatic breast cancer (MBC). METHODS: This retrospective study included 185 patients with newly diagnosed MBC evaluated between 2001 and 2007. CTCs were isolated and enumerated before patients started first-line treatment using the CellSearch system. Overall survival (OS) was calculated from the date of CTC measurement, estimated by the Kaplan-Meier product limit method, and compared between groups with the log-rank test. Cox proportional hazards models were fitted to determine the association between CTC levels and OS after controlling for other prognostic factors. RESULTS: The median age of the patients at the time of MBC diagnosis was 49 years. Fifty-six (30.3%) patients presented with de novo metastatic disease, and 129 (69.7%) presented with newly recurrent breast cancer. A total of 114 patients (61.6%) had CTC<5, and 71 (38.4%) had CTC >or= 5. The median OS was 28.3 months and 15 months (P< .0001) for patients with CTC<5 and CTC >or= 5, respectively. Superior survival among patients with CTC<5 was observed regardless of hormone receptor and HER-2/neu status, site of first metastases, or whether the patient had recurrent or de novo metastatic disease. In the multivariate model, patients with CTC >or= 5 had a hazards ratio of death of 3.64 (95% confidence interval, 2.11-6.30) compared with patients with CTC <5. CONCLUSIONS: The results of this large retrospective study confirms that CTCs are a strong independent predictor of survival among women with either de novo or newly recurrent MBC. CTCs should be considered as a new stratification method for women with newly diagnosed MBC.

Validation of reverse phase protein array for practical screening of potential biomarkers in serum and plasma: accurate detection of CA19-9 levels in pancreatic cancer.

The current study analyzed reverse phase protein arrays (RPPA) as a means to experimentally validate biomarkers in blood samples. One microliter samples of sera (n = 71), and plasma (n = 78) were serially diluted and printed on NC-coated slides. CA19-9 levels from RPPA results were compared with identical patient samples as measured by ELISA. There was a strong correlation between RPPA and ELISA (r = 0.87) as determined by scatter plots. Sample reproducibility of CA19-9 levels was excellent (interslide correlation r = 0.88; intraslide correlation r = 0.83). The ability of RPPA to accurately distinguish CA19-9 levels between cancer and noncancer samples were determined using receiver operating characteristic curves and compared with ELISA. The AUC for RPPA and ELISA was comparable (0.87 and 0.86, respectively). When the mean CA19-9 levels of normal samples was used as a cutoff for RPPA and compared with the standard clinical ELISA cutoff, comparable specificities (71% for both) were observed. Notably, RPPA samples normalized to albumin showed increased sensitivity compared to ELISA (90% vs. 75%). As RPPA is a high-throughput method that shows results comparable to that of ELISA, we propose that RPPA is a viable technique for rapid experimental screening and validation of candidate biomarkers in blood samples.