Of patients with new-onset diabetes (NOD; based on glycemic status) older than 50 years, approximately 1% are diagnosed with pancreatic cancer (PC) within 3 years. We aimed to develop and validate a ...model to determine risk of PC in patients with NOD.
We retrospectively collected data from 4 independent and nonoverlapping cohorts of patients (N = 1,561) with NOD (based on glycemic status; data collected at date of diagnosis and 12 months previously) in the Rochester Epidemiology Project from January 1, 2000 through December 31, 2015 to create our model. The model weighed scores for 3 factors identified in the discovery cohort to be most strongly associated with PC (64 patients with PC and 192 with type 2 diabetes): change in weight, change in blood glucose, and age at onset of diabetes. We called our model Enriching New-Onset Diabetes for Pancreatic Cancer (ENDPAC). We validated the locked-down model and cutoff score in an independent population-based cohort of 1,096 patients with diabetes; of these, 9 patients (82%) had PC within 3 years of meeting the criteria for NOD.
In the discovery cohort, the END-PAC model identified patients who developed PC within 3 years of diabetes onset (area under receiver operating characteristic curve 0.87); a score of at least 3 identified patients who developed PC with 80% sensitivity and specificity. In the validation cohort, a score of at least 3 identified 7 of 9 patients with PC (78%) with 85% specificity; the prevalence of PC in patients with a score of at least 3 (3.6%) was 4.4-fold greater than in patients with NOD. A high END-PAC score in patients who did not have PC (false positives) was often due to such factors as recent steroid use or different malignancy. An ENDPAC score no higher than 0 (in 49% of patients) meant that patients had an extremely low risk for PC. An END-PAC score of at least 3 identified 75% of patients in the discovery cohort more than 6 months before a diagnosis of PC.
Based on change in weight, change in blood glucose, and age at onset of diabetes, we developed and validated a model to determine risk of PC in patients with NOD based on glycemic status (END-PAC model). An independent prospective study is needed to further validate this model, which could contribute to early detection of PC.
Display omitted
Research methods for biomarker evaluation lag behind those for evaluating therapeutic treatments. Although a phased approach to development of biomarkers exists and guidelines are available for ...reporting study results, a coherent and comprehensive set of guidelines for study design has not been delineated. We describe a nested case–control study design that involves prospective collection of specimens before outcome ascertainment from a study cohort that is relevant to the clinical application. The biomarker is assayed in a blinded fashion on specimens from randomly selected case patients and control subjects in the study cohort. We separately describe aspects of the design that relate to the clinical context, biomarker performance criteria, the biomarker test, and study size. The design can be applied to studies of biomarkers intended for use in disease diagnosis, screening, or prognosis. Common biases that pervade the biomarker research literature would be eliminated if these rigorous standards were followed.
The aim of this study was to identify a biomarker that could improve alpha‐fetoprotein (AFP) performance in hepatocellular carcinoma (HCC) surveillance among patients with cirrhosis. We performed ...proteomic profiling of plasma from patients with cirrhosis or HCC and validated selected candidate HCC biomarkers in two geographically distinct cohorts to include HCC of different etiologies. Mass spectrometry profiling of highly fractionated plasma from 18 cirrhosis and 17 HCC patients identified osteopontin (OPN) as significantly up‐regulated in HCC cases, compared to cirrhosis controls. OPN levels were subsequently measured in 312 plasma samples collected from 131 HCC patients, 76 cirrhosis patients, 52 chronic hepatitis C (CHC) and B (CHB) patients, and 53 healthy controls in two independent cohorts. OPN plasma levels were significantly elevated in HCC patients, compared to cirrhosis, CHC, CHB, or healthy controls, in both cohorts. OPN alone or in combination with AFP had significantly better area under the receiver operating characteristic curve, compared to AFP, in comparing cirrhosis and HCC in both cohorts. OPN overall performance remained higher than AFP in comparing cirrhosis and the following HCC groups: HCV‐related HCC, HBV‐associated HCC, and early HCC. OPN also had a good sensitivity in AFP‐negative HCC. In a pilot prospective study including 22 patients who developed HCC during follow‐up, OPN was already elevated 1 year before diagnosis. Conclusion: OPN was more sensitive than AFP for the diagnosis of HCC in all studied HCC groups. In addition, OPN performance remained intact in samples collected 1 year before diagnosis. (HEPATOLOGY 2012)
Two-phase sampling designs, including nested case-control and case-cohort designs, are frequently utilized in large cohort studies involving expensive biomarkers. To analyze data from two-phase ...designs with a binary outcome, parametric models such as logistic regression are often adopted. However, when the model assumptions are not valid, parametric models may lead to biased estimation and risk evaluation. In this paper, we propose a robust semiparametric regression model for binary outcomes and an easy-to-implement computational procedure that combines the pool-adjacent violators algorithm with inverse probability weighting. The asymptotic properties are established, including consistency and the convergence rate. Simulation studies show that the proposed method performs well and is more robust than logistic regression methods. We demonstrate the application of the proposed method to real data from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial.
To investigate whether a panel of circulating protein biomarkers would improve risk assessment for lung cancer screening in combination with a risk model on the basis of participant characteristics.
...A blinded validation study was performed using prostate lung colorectal ovarian (PLCO) Cancer Screening Trial data and biospecimens to evaluate the performance of a four-marker protein panel (4MP) consisting of the precursor form of surfactant protein B, cancer antigen 125, carcinoembryonic antigen, and cytokeratin-19 fragment in combination with a lung cancer risk prediction model (PLCO
) compared with current US Preventive Services Task Force (USPSTF) screening criteria. The 4MP was assayed in 1,299 sera collected preceding lung cancer diagnosis and 8,709 noncase sera.
The 4MP alone yielded an area under the receiver operating characteristic curve of 0.79 (95% CI, 0.77 to 0.82) for case sera collected within 1-year preceding diagnosis and 0.74 (95% CI, 0.72 to 0.76) among the entire specimen set. The combined 4MP + PLCO
model yielded an area under the receiver operating characteristic curve of 0.85 (95% CI, 0.82 to 0.88) for case sera collected within 1 year preceding diagnosis. The benefit of the 4MP in the combined model resulted from improvement in sensitivity at high specificity. Compared with the USPSTF2021 criteria, the combined 4MP + PLCO
model exhibited statistically significant improvements in sensitivity and specificity. Among PLCO participants with ≥ 10 smoking pack-years, the 4MP + PLCO
model would have identified for annual screening 9.2% more lung cancer cases and would have reduced referral by 13.7% among noncases compared with USPSTF2021 criteria.
A blood-based biomarker panel in combination with PLCO
significantly improves lung cancer risk assessment for lung cancer screening.
We have developed herein a quantitative mass spectrometry-based approach to analyze the etiology-related alterations in fucosylation degree of serum haptoglobin in patients with liver cirrhosis and ...hepatocellular carcinoma (HCC). The three most common etiologies, including infection with hepatitis B virus (HBV), infection with hepatitis C virus (HCV), and heavy alcohol consumption (ALC), were investigated. Only 10 μL of serum was used in this assay in which haptoglobin was immunoprecipitated using a monoclonal antibody. The N-glycans of haptoglobin were released with PNGase F, desialylated, and permethylated prior to MALDI-QIT-TOF MS analysis. In total, N-glycan profiles derived from 104 individual patient samples were quantified (14 healthy controls, 40 cirrhosis, and 50 HCCs). A unique pattern of bifucosylated tetra-antennary glycan, with both core and antennary fucosylation, was identified in HCC patients. Quantitative analysis indicated that the increased fucosylation degree was highly associated with HBV- and ALC-related HCC patients compared to that of the corresponding cirrhosis patients. Notably, the bifucosylation degree was distinctly increased in HCC patients versus that in cirrhosis of all etiologies. The elevated bifucosylation degree of haptoglobin can discriminate early stage HCC patients from cirrhosis in each etiologic category, which may be used to provide a potential marker for early detection and to predict HCC in patients with cirrhosis.
Given the limited sensitivity and specificity of prostate-specific antigen (PSA), its widespread use as a screening tool has raised concerns for the overdiagnosis of low-risk and the underdiagnosis ...of high-grade prostate cancer. To improve early-detection biopsy decisions, the National Cancer Institute conducted a prospective validation trial to assess the diagnostic performance of the prostate cancer antigen 3 (PCA3) urinary assay for the detection of prostate cancer among men screened with PSA.
In all, 859 men (mean age, 62 years) from 11 centers scheduled for a diagnostic prostate biopsy between December 2009 and June 2011 were enrolled. The primary outcomes were to assess whether PCA3 could improve the positive predictive value (PPV) for an initial biopsy (at a score > 60) and the negative predictive value (NPV) for a repeat biopsy (at a score < 20).
For the detection of any cancer, PPV was 80% (95% CI, 72% to 86%) in the initial biopsy group, and NPV was 88% (95% CI, 81% to 93%) in the repeat biopsy group. The addition of PCA3 to individual risk estimation models (which included age, race/ethnicity, prior biopsy, PSA, and digital rectal examination) improved the stratification of cancer and of high-grade cancer.
These data independently support the role of PCA3 in reducing the burden of prostate biopsies among men undergoing a repeat prostate biopsy. For biopsy-naive patients, a high PCA3 score (> 60) significantly increases the probability that an initial prostate biopsy will identify cancer.
Many cancer biomarker research studies seek to develop markers that can accurately detect or predict future onset of disease. To design and evaluate these studies, one must specify the levels of ...accuracy sought. However, justified target levels are rarely available.
We describe a way to calculate target levels of sensitivity and specificity for a biomarker intended to be applied in a defined clinical context. The calculation requires knowledge of the prevalence or incidence of cases in the clinical population and the ratio of benefit associated with the clinical consequences of a positive biomarker test in cases (true positive) to cost associated with a positive biomarker test in controls (false positive). Guidance is offered on soliciting the cost/benefit ratio. The calculations are based on the longstanding decision theory concept of providing a net benefit on average in the population, and they rely on some assumptions about uniformity of costs and benefits to those tested.
Calculations are illustrated with 3 applications: predicting colon cancer recurrence in stage 1 patients; predicting interval breast cancer (between mammography screenings); and screening for ovarian cancer.
It is feasible to specify target levels of biomarker performance that enable evaluation of the potential clinical impact of biomarkers in early-phase studies. Nevertheless, biomarkers meeting the criteria should still be tested rigorously in studies that measure the actual impact on patient outcomes of using the biomarker to make clinical decisions.
Hepatocellular carcinoma (HCC) has limited treatment options when diagnosed at advanced stages; therefore, early detection is critical to reduce mortality. There is disagreement about the value of ...α-fetoprotein (AFP) in HCC surveillance. We aim to improve the sensitivity of AFP in HCC surveillance by using an algorithm that incorporates screening history to define patient-specific thresholds for positive a screen.
De-identified data from the Hepatitis C Antiviral Long-term Treatment against Cirrhosis (HALT-C) trial, which enrolled 1050 patients with hepatitis C and advanced fibrosis or cirrhosis who were prospectively followed every 3-6 months, were analyzed. AFP was assayed at each visit, and ultrasonography was performed every 6-12 months. A panel adjudicated the diagnosis of HCC. A parametric empirical Bayes (PEB) screening algorithm, which incorporates screening history, was compared with a single threshold approach for interpreting AFP results.
During a median follow-up of 80 months, 88 patients (48 of 427 with cirrhosis and 40 of 621 with advanced fibrosis) were diagnosed with HCC. PEB improved the sensitivity of AFP for detecting all HCC from 60.4% to 77.1% (P < .0005) in patients with cirrhosis and from 72.5% to 87.5% (P = .0015) in patients with advanced fibrosis, when the false-positive rate among all screenings was set at 10%. PEB algorithm detected HCC 1.7-1.9 years earlier in the cirrhosis group and 1.4-1.7 years earlier in the advanced fibrosis group, compared with single threshold approach.
PEB increases the sensitivity of AFP testing and detects HCC earlier among hepatitis C patients with advanced fibrosis or cirrhosis. These data should prompt a reevaluation of how AFP is used in combination with ultrasound in HCC surveillance.
PDF
