Health State Utilities Associated with False-Positive Cancer Screening Results.

INTRODUCTION: Early cancer detection can significantly improve patient outcomes and reduce mortality rates. Novel cancer screening approaches, including multi-cancer early detection tests, have been developed. Cost-utility analyses will be needed to examine their value, and these models require health state utilities. The purpose of this study was to estimate the disutility (i.e., decrease in health state utility) associated with false-positive cancer screening results. METHODS: In composite time trade-off interviews using a 1-year time horizon, UK general population participants valued 10 health state vignettes describing cancer screening with true-negative or false-positive results. Each false-positive vignette described a common diagnostic pathway following a false-positive result suggesting lung, colorectal, breast, or pancreatic cancer. Every pathway ended with a negative result (no cancer detected). The disutility of each false positive was calculated as the difference between the true-negative and each false-positive health state, and because of the 1-year time horizon, each disutility can be interpreted as a quality-adjusted life-year decrement associated with each type of false-positive experience. RESULTS: A total of 203 participants completed interviews (49.8% male; mean age = 42.0 years). The mean (SD) utility for the health state describing a true-negative result was 0.958 (0.065). Utilities for false-positive health states ranged from 0.847 (0.145) to 0.932 (0.059). Disutilities for false positives ranged from - 0.031 to - 0.111 (- 0.041 to - 0.111 for lung cancer; - 0.079 for colorectal cancer; - 0.031 to - 0.067 for breast cancer; - 0.048 to - 0.088 for pancreatic cancer). CONCLUSION: All false-positive results were associated with a disutility. Greater disutility was associated with more invasive follow-up diagnostic procedures, longer duration of uncertainty regarding the eventual diagnosis, and perceived severity of the suspected cancer type. Utility values estimated in this study would be useful for economic modeling examining the value of cancer screening procedures.

Blood-based tests for multicancer early detection (PATHFINDER): a prospective cohort study.

BACKGROUND: Multicancer early detection (MCED) blood tests can detect a cancer signal from circulating cell-free DNA (cfDNA). PATHFINDER was a prospective cohort study investigating the feasibility of MCED testing for cancer screening. METHODS: In this prospective cohort study done in oncology and primary care outpatient clinics at seven US health networks, a convenience sample of adults aged 50 years or older without signs or symptoms of cancer consented to MCED testing. We collected blood, analysed cfDNA, and returned results to participants' doctors. If a methylation signature indicative of cancer was detected, predicted cancer signal origin(s) informed diagnostic assessment. The primary outcome was time to, and extent of, diagnostic testing required to confirm the presence or absence of cancer. This trial is registered at ClinicalTrials.gov, NCT04241796, and is completed. FINDINGS: Between Dec 12, 2019, and Dec 4, 2020, we recruited 6662 participants. 4204 (63·5%) of 6621 participants with analysable results were women, 2417 (36·5%) were men, and 6071 (91·7%) were White. A cancer signal was detected in 92 (1·4%) of 6621 participants with analysable results. 35 (38%) participants were diagnosed with cancer (true positives) and 57 (62%) had no cancer diagnosis (false positives). Excluding two participants whose diagnostic assessments began before MCED test results were reported, median time to diagnostic resolution was 79 days (IQR 37-219): 57 days (33-143) in true-positive and 162 days (44-248) in false-positive participants. Most participants had both laboratory tests (26 [79%] of 33 with true-positive results and 50 [88%] of 57 with false-positive results) and imaging (30 [91%] of 33 with true-positive results and 53 [93%] of 57 with false-positive results). Fewer procedures were done in participants with false-positive results (17 [30%] of 57) than true-positive results (27 [82%] of 33) and few had surgery (one with a false-positive result and three with a true-positive result). INTERPRETATION: This study supports the feasibility of MCED screening for cancer and underscores the need for further research investigating the test's clinical utility. FUNDING: GRAIL.

Patient Preferences for Multi-Cancer Early Detection (MCED) Screening Tests.

BACKGROUND: Emerging blood-based multi-cancer early detection (MCED) tests can detect a variety of cancer types across stages with a range of sensitivity, specificity, and ability to predict the origin of the cancer signal. However, little is known about the general US population's preferences for MCED tests. OBJECTIVE: To quantify preferences for MCED tests among US adults aged 50-80 years using a discrete choice experiment (DCE). METHODS: To quantify preferences for attributes of blood-based MCED tests, an online DCE was conducted with five attributes (true positives, false negatives, false positives, likelihood of the cancer type unknown, number of cancer types detected), among the US population aged 50-80 years recruited via online panels and social media. Data were analyzed using latent class multinomial logit models and relative attribute importance was obtained. RESULTS: Participants (N = 1700) were 54% female, mean age 63.3 years. Latent class modeling identified three classes with distinct preferences for MCED tests. The rank order of attribute importance based on relative attribute importance varied by latent class, but across all latent classes, participants preferred higher accuracy (fewer false negatives and false positives, more true positives) and screenings that detected more cancer types and had a lower likelihood of cancer type unknown. Overall, 72% of participants preferred to receive an MCED test in addition to currently recommended cancer screenings. CONCLUSIONS: While there is significant heterogeneity in cancer screening preferences, the majority of participants preferred MCED screening and the accuracy of these tests is important. While the majority of participants preferred adding an MCED test to complement current cancer screenings, the latent class analyses identified a small (16%) and specific subset of individuals who value attributes differently, with particular concern regarding false-negative and false-positive test results, who are significantly less likely to opt-in.

Evaluation of cell-free DNA approaches for multi-cancer early detection.

In the Circulating Cell-free Genome Atlas (NCT02889978) substudy 1, we evaluate several approaches for a circulating cell-free DNA (cfDNA)-based multi-cancer early detection (MCED) test by defining clinical limit of detection (LOD) based on circulating tumor allele fraction (cTAF), enabling performance comparisons. Among 10 machine-learning classifiers trained on the same samples and independently validated, when evaluated at 98% specificity, those using whole-genome (WG) methylation, single nucleotide variants with paired white blood cell background removal, and combined scores from classifiers evaluated in this study show the highest cancer signal detection sensitivities. Compared with clinical stage and tumor type, cTAF is a more significant predictor of classifier performance and may more closely reflect tumor biology. Clinical LODs mirror relative sensitivities for all approaches. The WG methylation feature best predicts cancer signal origin. WG methylation is the most promising technology for MCED and informs development of a targeted methylation MCED test.

The PATHFINDER Study: Assessment of the Implementation of an Investigational Multi-Cancer Early Detection Test into Clinical Practice.

To examine the extent of the evaluation required to achieve diagnostic resolution and the test performance characteristics of a targeted methylation cell-free DNA (cfDNA)-based multi-cancer early detection (MCED) test, ~6200 participants ≥50 years with (cohort A) or without (cohort B) ≥1 of 3 additional specific cancer risk factors will be enrolled in PATHFINDER (NCT04241796), a prospective, longitudinal, interventional, multi-center study. Plasma cfDNA from blood samples will be analyzed to detect abnormally methylated DNA associated with cancer (i.e., cancer "signal") and a cancer signal origin (i.e., tissue of origin). Participants with a "signal detected" will undergo further diagnostic evaluation per guiding physician discretion; those with a "signal not detected" will be advised to continue guideline-recommended screening. The primary objective will be to assess the number and types of subsequent diagnostic tests needed for diagnostic resolution. Based on microsimulations (using estimates of cancer incidence and dwell times) of the typical risk profiles of anticipated participants, the median (95% CI) number of participants with a "signal detected" result is expected to be 106 (87-128). Subsequent diagnostic evaluation is expected to detect 52 (39-67) cancers. The positive predictive value of the MCED test is expected to be 49% (39-58%). PATHFINDER will evaluate the integration of a cfDNA-based MCED test into existing clinical cancer diagnostic pathways. The study design of PATHFINDER is described here.

Prognostic Significance of Blood-Based Multi-cancer Detection in Plasma Cell-Free DNA.

PURPOSE: We recently reported the development of a cell-free DNA (cfDNA) targeted methylation (TM)-based sequencing approach for a multi-cancer early detection (MCED) test that includes cancer signal origin prediction. Here, we evaluated the prognostic significance of cancer detection by the MCED test using longitudinal follow-up data. EXPERIMENTAL DESIGN: As part of a Circulating Cell-free Genome Atlas (CCGA) substudy, plasma cfDNA samples were sequenced using a TM approach, and machine learning classifiers predicted cancer status and cancer signal origin. Overall survival (OS) of cancer participants in the first 3 years of follow-up was evaluated in relation to cancer detection by the MCED test and clinical characteristics. RESULTS: Cancers not detected by the MCED test had significantly better OS (P < 0.0001) than cancers detected, even after accounting for other covariates, including clinical stage and method of clinical diagnosis (i.e., standard-of-care screening or clinical presentation with signs/symptoms). Additionally, cancers not detected by the MCED test had better OS than was expected when data were adjusted for age, stage, and cancer type from the Surveillance, Epidemiology, and End Results (SEER) program. In cancers with current screening options, the MCED test also differentiated more aggressive cancers from less aggressive cancers (P < 0.0001). CONCLUSIONS: Cancer detection by the MCED test was prognostic beyond clinical stage and method of diagnosis. Cancers not detected by the MCED test had better prognosis than cancers detected and SEER-based expected survival. Cancer detection and prognosis may be linked by the underlying biological factor of tumor fraction in cfDNA.

An observational study of the impact of genetic testing for pain perception in the clinical management of chronic non-cancer pain.

OBJECTIVE: Pain levels are a key metric in clinical care. However, the assessment of pain is limited to basic questionnaires and physician interpretation, which yield subjective data. Genetic markers of pain sensitivity, such as single nucleotide polymorphisms in the catechol-O-methyltransferase gene, have been shown to be associated with pain perception and have been used to provide objective information about a patient's pain. The goal of this study was to determine if physician treatment adjustments based on genetic tests of pain perception resulted in improved outcomes for patients. MATERIAL AND METHODS: A prospective, longitudinal study was conducted with 134 chronic non-cancer pain patients genotyped for pain perception-related catechol-O-methyltransferase haplotypes. Physicians were provided with patients' results and asked to document 1) their assessment of benefit of the genetic test; 2) treatment changes made based on the genetic test; and 3) patient clinical responses to changes implemented. RESULTS: Based on genetic testing results, physicians adjusted treatment plans for 40% of patients. When medication changes were made based on genetic testing results, 72% of patients showed improvement in clinical status. When non-pharmacological actions were performed, 69% of physicians felt their patients' clinical status improved. Moreover, physicians believed the genetic test results were consistent with patient pain levels in 85% of cases. CONCLUSIONS: These results demonstrate that providing personalized medicine with genetic information related to pain perception affected physician clinical decision-making for a substantial proportion of patients in this study, and that the availability and utilization of this information was a contributing factor in clinical improvement.

Clinical performance of the CytoScan Dx Assay in diagnosing developmental delay/intellectual disability.

PURPOSE: The prevalence of developmental disabilities in the United States is reported to be 13.87% across all racial, ethnic, and socioeconomic groups. Microarrays have been recommended as first-tier tests for these patients. This study reports the diagnostic yield and potential actionability of findings using a high-density chromosomal microarray (CMA). METHODS: The diagnostic yield of CytoScan Dx Assay in 960 patients was assessed with the Riggs criteria of actionability to evaluate predicted clinical utility. RESULTS: Eighty-six percent of the subjects were assessed using a microarray as part of historical routine patient care (RPC). The rate of pathogenic findings was similar between RPC (13.3%) and the CytoScan Dx Assay (13.8%). Among the 138 patients who did not receive microarray as RPC, the diagnostic yield for CytoScan Dx Assay was 23.9% as compared with 14.5%, indicating a 9.4% improvement when using higher-resolution methods. Thirty-five percent of patients with abnormal findings had predicted clinical management implications. CONCLUSIONS: This is the first study to assess the clinical performance of CytoScan Dx Assay. The assay's diagnostic yields are similar to those found in other studies of CMAs. Thirty-five percent of patients with abnormal findings are predicted to have clinical management implications that may improve health outcomes.

Disseminated Medulloblastoma in a Child with Germline BRCA2 6174delT Mutation and without Fanconi Anemia.

Medulloblastoma, the most common malignant brain tumor in children, occurs with increased frequency in individuals with Fanconi anemia who have biallelic germline mutations in BRCA2. We describe an 8-year-old child who had disseminated anaplastic medulloblastoma and a deleterious heterozygous BRCA2 6174delT germline mutation. Molecular profiling was consistent with Group 4 medulloblastoma. The posterior fossa mass was resected and the patient received intensive chemotherapy and craniospinal irradiation. Despite this, the patient succumbed to a second recurrence of his medulloblastoma, which presented 8 months after diagnosis as malignant pleural and peritoneal effusions. Continuous medulloblastoma cell lines were isolated from the original tumor (CHLA-01-MED) and the malignant pleural effusion (CHLA-01R-MED). Here, we provide their analyses, including in vitro and in vivo growth, drug sensitivity, comparative genomic hybridization, and next generation sequencing analysis. In addition to the BRCA2 6174delT, the medulloblastoma cells had amplification of MYC, deletion at Xp11.2, and isochromosome 17, but no structural variations or overexpression of GFI1 or GFI1B. To our knowledge, this is the first pair of diagnosis/recurrence medulloblastoma cell lines, the only medulloblastoma cell lines with BRCA2 6174delT described to date, and the first reported case of a child with medulloblastoma associated with a germline BRCA2 6174delT who did not also have Fanconi anemia.

Clinical utility of chromosomal microarray analysis in the diagnosis and management of monosomy 7 mosaicism.

There have been dramatic improvements in our ability to more accurately diagnose the underlying genetic causes of developmental delay/intellectual disability; however, there is less known about the treatment trajectory and whether or not patient management and outcomes have changed due to the information gained from genetic testing. Here we report a case study of a 20-month-old male first referred to the genetics clinic in 2008 for interhemispheric cysts, agenesis of the corpus callosum, left cortical dysplasia, and developmental delay of unknown etiology. The diagnostic work-up for this patient included chromosomal microarray which detected >20% mosaicism for monosomy 7, which raised concern for a possible myelodysplastic syndrome. The clone was not detected in stimulated peripheral blood cultures and his karyotype was reported as a normal male. Because of this microarray finding, he was referred to pediatric hematology/oncology where he was confirmed to have a pre-symptomatic diagnosis of myelodysplastic syndrome and was treated with chemotherapy and a bone-marrow transplant. This case illustrates the clinical utility of microarray testing and the importance of long-term follow-up to assess patient outcomes.

Discovery of serum biomarkers of ovarian cancer using complementary proteomic profiling strategies.

PURPOSE: Ovarian cancer is a devastating disease and biomarkers for its early diagnosis are urgently required. Serum may be a valuable source of biomarkers that may be revealed by proteomic profiling. Herein, complementary serum protein profiling strategies were employed for discovery of biomarkers that could discriminate cases of malignant and benign ovarian cancer. EXPERIMENTAL DESIGN: Identically collected and processed serum samples from 22 cases of invasive epithelial ovarian cancer, 45 benign ovarian neoplasms, and 64 healthy volunteers were subjected to immunodepletion and protein equalization coupled to 2D-DIGE/MS and multidimensional fractionation coupled to SELDI-TOF profiling with MS/MS for protein identification. Selected candidates were verified by ELISA in samples from malignant (n = 70) and benign (n = 89) cases and combined marker panels tested against serum CA125. RESULTS: Both profiling platforms were complementary in identifying biomarker candidates, four of which (A1AT, SLPI, APOA4, VDBP) significantly discriminated malignant from benign cases. However, no combination of markers was as good as CA125 for diagnostic accuracy. SLPI was further tested as an early marker using prediagnosis serum samples. While it rose in cases toward diagnosis, it did not discriminate prediagnosis cases from controls. CONCLUSIONS AND CLINICAL RELEVANCE: The candidate biomarkers warrant further validation in independent sample sets.

Early inflammatory response in epithelial ovarian tumor cyst fluids.

Mortality rates for epithelial ovarian cancer (EOC) are high, mainly due to late-stage diagnosis. The identification of biomarkers for this cancer could contribute to earlier diagnosis and increased survival rates. Given that chronic inflammation plays a central role in cancer initiation and progression, we selected and tested 15 cancer-related cytokines and growth factors in 38 ovarian cyst fluid samples. We used ovarian cyst fluid since it is found in proximity to the pathology and mined it for inflammatory biomarkers suitable for early detection of EOC. Immunoprecipitation and high-throughput sample fractionation were obtained by using tandem antibody libraries bead and mass spectrometry. Two proteins, monocyte chemoattractant protein-1 (MCP-1/CCL2) and interleucin-8 (IL-8/CXCL8), were significantly (P < 0.0001) higher in the malignant (n = 16) versus benign (n = 22) tumor cysts. Validation of MCP-1, IL-8, and growth-regulated protein-α (GROα/CXCL1) was performed with ELISA in benign, borderline, and malignant cyst fluids (n = 256) and corresponding serum (n = 256). CA125 was measured in serum from all patients and used in the algorithms performed. MCP-1, IL-8, and GROα are proinflammatory cytokines and promoters of tumor growth. From 5- to 100-fold higher concentrations of MCP-1, IL-8 and GROα were detected in the cyst fluids compared to the serum. Significant (P < 0.001) cytokine response was already established in borderline cyst fluids and stage I EOC. In serum a significant (P < 0.01) increase of IL-8 and GROα was found, but not until stage I and stage III EOC, respectively. These findings confirm that early events in tumorigenesis can be analyzed and detected in the tumor environment and we conclude that ovarian cyst fluid is a promising source in the search for new biomarkers for early ovarian tumors.

Clinical performance of a multivariate index assay for detecting early-stage ovarian cancer.

OBJECTIVE: We sought to analyze the effectiveness of a multivariate index assay (MIA) in identifying early-stage ovarian malignancy compared to clinical assessment, CA 125-II, and modified American Congress of Obstetricians and Gynecologists (ACOG) guidelines among women undergoing surgery for an adnexal mass. STUDY DESIGN: Patients were recruited in 2 related prospective, multi-institutional trials involving 44 sites. All women had preoperative imaging and biomarker analysis. Preoperative biomarker values, physician assessment of ovarian cancer risk, and modified ACOG guideline risk stratification were correlated with surgical pathology. RESULTS: A total of 1016 patients were evaluable for MIA, CA 125-II, and clinical assessment. Overall, 86 patients (8.5%) had primary-stage I/II primary ovarian malignancy, with 70.9% having stage I disease and 29.1% having stage II disease. For all early-stage ovarian malignancies, MIA combined with clinical assessment had significantly higher sensitivity (95.3%; 95% confidence interval [CI], 88.6-98.2) compared to clinical assessment alone (68.6%; 95% CI, 58.2-77.4), CA 125-II (62.8%; 95% CI, 52.2-72.3), and modified ACOG guidelines (76.7%; 95% CI, 66.8-84.4) (P < .0001). Among the 515 premenopausal patients, the sensitivity for early-stage ovarian cancer was 89.3% (95% CI, 72.8-96.3) for MIA combined with clinical assessment, 60.7% (95% CI, 42.4-76.4) for clinical assessment alone, 35.7% (95% CI, 20.7-54.2) for CA 125-II, and 78.6% (95% CI, 60.5-89.8) for modified ACOG guidelines. Early-stage ovarian cancer in postmenopausal patients was correctly detected in 98.3% (95% CI, 90.9-99.7) of cases by MIA combined with clinical assessment, compared to 72.4% (95% CI, 59.8-82.2) for clinical assessment alone, 75.9% (95% CI, 63.5-85.0) for CA 125-II, and 75.9% (95% CI, 63.5-85.0) for modified ACOG guidelines. CONCLUSION: MIA combined with clinical assessment demonstrated higher sensitivity for early-stage ovarian malignancy compared to clinical assessment alone, CA 125-II, and modified ACOG guidelines with consistent performance across menopausal status.

Impact of a multivariate index assay on referral patterns for surgical management of an adnexal mass.

OBJECTIVE: To determine the impact on referral patterns of using a Multivariate Index Assay, CA125, modified-American College of Obstetricians and Gynecologists referral guidelines, and clinical assessment among patients undergoing surgery for an adnexal mass after initial evaluation by nongynecologic oncologists. STUDY DESIGN: Overall, 770 patients were enrolled by nongynecologic oncologists from 2 related, multiinstitutional, prospective trials and analyzed retrospectively. All patients had preoperative imaging and biomarker analysis. The subset of patients enrolled by nongynecologic oncologists was analyzed to determine the projected referral patterns and sensitivity for malignancy based on multivariate index assay (MIA), CA125, modified-American College of Obstetricians and Gynecologists (ACOG) guidelines, and clinical assessment compared with actual practice. RESULTS: The prevalence of malignancy was 21.3% (n = 164). In clinical practice, 462/770 patients (60.0%) were referred to a gynecologic oncologist for surgery. Triage based on CA125 predicted referral of 157/770 patients (20.4%) with sensitivity of 68.3% (95% confidence interval [CI], 60.8-74.9). Triage based on modified-ACOG guidelines would have resulted in referral of 256/770 patients (33.2%) with a sensitivity of 79.3% (95% CI, 72.4-84.8). Clinical assessment predicted referral of 184/763 patients (24.1%) with a sensitivity of 73.2% (95% CI, 65.9-79.4). Risk stratification using multivariate index assay would have resulted in referral of 429/770 (55.7%) patients, with sensitivity of 90.2% (95% CI, 84.7-93.9). MIA demonstrated statistically significant higher sensitivity (P < .0001) and lower specificity (P < .0001) for detecting malignancy compared with clinical assessment, CA125, and modified-ACOG guidelines. CONCLUSION: In this study population, use of MIA as a risk stratification test was associated with referral patterns by nongynecologic oncologists comparable to actual clinical practice and higher sensitivity for malignancy than other adnexal mass triage algorithms.

Ovarian cyst fluids are a cache of tumor biomarkers that include calgranulin A and calgranulin B isoforms.

SELDI-TOF MS analysis of cyst fluids identified 95 peaks that discriminate malignant, borderline, and benign ovarian tumors. Three prominent peaks, which correspond to calgranulin A (m/z 10847) and two isoforms of calgranulin B (m/z 12717 and 13294), have higher concentrations in borderline and malignant cyst fluids. Together, calgranulin A and B distinguish borderline and malignant tumors from benign tumors with 28.6% and 63.6% sensitivity for early stage disease, respectively, at 95% specificity and with 74.8% accuracy. Ovarian cyst fluids are useful for discovering discriminatory biomarkers, such as calgranulin, which may have utility for detecting, diagnosing, and biochemically classifying ovarian tumors.

Apolipoprotein concentrations are elevated in malignant ovarian cyst fluids suggesting that lipoprotein metabolism is dysregulated in epithelial ovarian cancer.

SELDI-TOF MS analysis of ovarian cyst fluids revealed that peaks m/z 8696 and 8825 discriminate malignant, borderline, and benign tumors. These peaks correspond to isoforms of apoA2. ELISA demonstrates that apoA1, A2, B, C2, C3, and E cyst fluid concentrations are uncorrelated and higher in malignant ovarian tumors, but only apoA2, apoE, and age are independent classifiers of malignant ovarian tumors, yielding 55.1% sensitivity, 95% specificity, and 88.1% accuracy to discern malignant from benign and borderline tumors. These data suggest that lipoprotein metabolism is dysregulated in ovarian cancer and that apoA2 and apoE warrant further investigation as ovarian tumor biomarkers.

Ovarian malignancy risk stratification of the adnexal mass using a multivariate index assay.

OBJECTIVE: To validate the effectiveness of a multivariate index assay in identifying ovarian malignancy compared to clinical assessment and CA125-II, among women undergoing surgery for an adnexal mass after enrollment by non-gynecologic oncology providers. METHODS: A prospective, multi-institutional trial enrolled female patients scheduled to undergo surgery for an adnexal mass from 27 non-gynecologic oncology practices. Pre-operative serum samples and physician assessment of ovarian cancer risk were correlated with final surgical pathology. RESULTS: A total of 494 subjects were evaluable for multivariate index assay, CA125-II, and clinical impression. Overall, 92 patients (18.6%) had a pelvic malignancy. Primary ovarian cancer was diagnosed in 65 patients (13.2%), with 43.1% having FIGO stage I disease. For all ovarian malignancies, the sensitivity of the multivariate index assay was 95.7% (95%CI=89.3-98.3) when combined with clinical impression. The multivariate index assay correctly predicted ovarian malignancy in 91.4% (95%CI=77.6-97.0) of cases of early-stage disease, compared to 65.7% (95%CI=49.2-79.2) for CA125-II. The multivariate index assay correctly identified 83.3% malignancies missed by clinical impression and 70.8% cases missed by CA125-II. Multivariate index assay was superior in predicting the absence of an ovarian malignancy, with a negative predictive value of 98.1% (95%CI=95.2-99.2). Both clinical impression and CA125-II were more accurate at identifying benign disease. The multivariate index assay correctly predicted benign pathology in 204 patients (50.7%, 95%CI=45.9-55.6) when combined with clinical impression. CONCLUSION: The multivariate index assay demonstrated higher sensitivity and negative predictive value for ovarian malignancy compared to clinical impression and CA125-II in an intended-use population of non-gynecologic oncology practices.

Ovarian cyst fluid is a rich proteome resource for detection of new tumor biomarkers.

BACKGROUND: We aimed to investigate the use of ovarian cyst fluid as a source for biomarker discovery and to find novel biomarkers for use in the diagnosis of epithelial ovarian tumors. RESULTS: Ovarian cyst fluids from 218 women were collected and 192 (benign n = 129, malignant n = 63) were analyzed using mass spectrometry. 1180 peaks were detected, 221 of which were differently expressed between benign and malignant ovarian tumors. Seventeen peaks had receiver operating curve and area under the curve values >0.70; the majority of these represented peaks for apolipoproteins C-III and C-I (ApoC-I), transthyretin (TTR), serum amyloid A4 (SAA4), and protein C inhibitor (PCI). ApoC-III, PCI, and serum CA125, with an ROC AUC 0.94 was the best combination for diagnosing epithelial ovarian cancer. ApoC-III and PCI was analyzed with ELISA in the original cohort (n = 40) and in 40 new cyst fluid samples for confirmation with an independent method and validation. Results from MS and ELISA for ApoC-III correlated well (p = 0.04). In the validation set, ApoC-III was significantly (p = 0.001) increased in the malignant epithelial ovarian cancers. CONCLUSIONS: Fluid from ovarian cysts connected directly to the primary tumor harbor many possible new tumor-specific biomarkers. Biomarkers found in ovarian cyst fluid may be used as molecular imaging targets for early diagnostics and prediction of therapy. Plasma abundant proteins are also influencing the cystic fluid proteome. Methods for isolating less frequent cyst fluid proteins are needed.

A validated biomarker panel to identify peripheral artery disease.

Current guidelines recommend obtaining an ankle-brachial index (ABI) to screen for peripheral artery disease (PAD) in subjects at risk. Previous work demonstrated that a combination of ß(2)-microglobulin, cystatin C, high-sensitivity C-reactive protein and glucose was associated with PAD. This study evaluated the ability of these biomarkers combined with clinical parameters to predict PAD in at-risk subjects. This study enrolled 1025 subjects from 99 primary care clinics who were smokers and/or diabetics ≥ 50 years or any individual ≥ 70 years. Consented subjects underwent a clinical assessment, fasting blood draw, and an ABI measurement with PAD defined as an ABI < 0.90 in either leg. The biomarkers and their interactions were evaluated using logistic regression and performance was evaluated at a cut point of the biomarker panel selected to maximize sensitivity while minimizing the false positive rate of the test. Of the 1025 subjects enrolled, 46 did not meet the ABI or other criteria for inclusion in the analysis. Among the evaluable subjects (n = 979), PAD was detected in 83 (8.5%). The model had a C-statistic of 0.73 (95% CI 0.67-0.79). There were 20 patients with PAD who were judged to be at low to moderate risk for cardiovascular events by clinical assessment; the model correctly identified 17 of these 20 patients. The model also performed well in subjects with no prior history of PAD. Thus, a biomarker panel may have a role for identifying PAD.

Proteomic biomarkers in combination with CA 125 for detection of epithelial ovarian cancer using prediagnostic serum samples from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial.

BACKGROUND: When epithelial ovarian cancer is detected at an early stage (I-II), the 5-year survival rate is between 70% and 90%; whereas, when it is detected in late stages (III-IV), the 5-year survival rate slips to <30%. In a previous report, the authors observed that proteomic biomarkers and cancer antigen 125 (CA 125) exhibited a sensitivity of 84% at a specificity of 98% for identifying sera from patients who had stage I disease at the time of surgery, significantly improving the sensitivity of CA 125 alone. The challenge, however, is to detect ovarian cancer before clinical diagnosis. The current study was part of a large effort to compare different multimarker biomarker panels for the early detection of ovarian cancer. Several biomarkers were evaluated alone and in combination with CA 125 in prediagnostically collected sera from women in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. METHODS: Proximal prediagnostic sera from 118 women with ovarian cancer (cases) and from 951 age-matched women (controls) (8 controls per case, including 4 randomly selected from the general population, 2 with CA 125 levels ≥ 35 U/mL, and 2 with a positive family history of breast/ovarian cancer) were analyzed using the CA 125 immunoassay and surface-enhanced laser desorption and ionization time-of-flight mass spectrometry to measure 7 proteins (apolipoprotein A1, truncated transthyretin, transferrin, hepcidin, ß-2 microglobulin, connective tissue activating protein III), and interalpha-trypsin inhibitor heavy-chain 4). Data were analyzed by 2 statistical strategies that combined the 7 markers and CA 125 into 1 predictive score for disease classification. RESULTS: CA 125 levels were elevated (≥ 35 U/mL) in 61.5% of 65 patients who had CA 125 data available from samples that were collected <12 months before cancer diagnosis; however, levels of the additional 7 biomarkers were not different between cases and the 3 control groups individually or combined. Two panels that combined CA 125 and the 7 biomarkers failed to improve the sensitivity of CA 125 alone. CONCLUSIONS: In contrast to earlier findings from analyzes of postdiagnostically collected sera, the addition of 7 biomarkers to CA 125 did not improve sensitivity for preclinical diagnosis beyond CA 125 alone.