Transforming epidemiology for 21st century medicine and public health

In 2012, the National Cancer Institute (NCI) engaged the scientific community to provide a vision for cancer epidemiology in the 21st century. Eight overarching thematic recommendations, with proposed corresponding actions for consideration by funding agencies, professional societies, and the research community emerged from the collective intellectual discourse. The themes are (i) extending the reach of epidemiology beyond discovery and etiologic research to include multilevel analysis, intervention evaluation, implementation, and outcomes research; (ii) transforming the practice of epidemiology by moving toward more access and sharing of protocols, data, metadata, and specimens to foster collaboration, to ensure reproducibility and replication, and accelerate translation; (iii) expanding cohort studies to collect exposure, clinical, and other information across the life course and examining multiple health-related endpoints; (iv) developing and validating reliable methods and technologies to quantify exposures and outcomes on a massive scale, and to assess concomitantly the role of multiple factors in complex diseases; (v) integrating "big data" science into the practice of epidemiology; (vi) expanding knowledge integration to drive research, policy, and practice; (vii) transforming training of 21st century epidemiologists to address interdisciplinary and translational research; and (viii) optimizing the use of resources and infrastructure for epidemiologic studies. These recommendations can transform cancer epidemiology and the field of epidemiology, in general, by enhancing transparency, interdisciplinary collaboration, and strategic applications of new technologies. They should lay a strong scientific foundation for accelerated translation of scientific discoveries into individual and population health benefits.

Cultivating cohort studies for observational translational research

BACKGROUND

"Discovery" research about molecular markers for diagnosis, prognosis, or prediction of response to therapy has frequently produced results that were not reproducible in subsequent studies. What are the reasons, and can observational cohorts be cultivated to provide strong and reliable answers to those questions? Experimental

METHODS

Selected examples are used to illustrate: (i) what features of research design provide strength and reliability in observational studies about markers of diagnosis, prognosis, and response to therapy? (ii) How can those design features be cultivated in existing observational cohorts, for example, within randomized controlled clinical trial (RCT), other existing observational research studies, or practice settings like health maintenance organization (HMOs)?

RESULTS

Examples include a study of RNA expression profiles of tumor tissue to predict prognosis of breast cancer, a study of serum proteomics profiles to diagnose ovarian cancer, and a study of stool-based DNA assays to screen for colon cancer. Strengths and weaknesses of observational study design features are discussed, along with lessons about how features that help assure strength might be "cultivated" in the future.

CONCLUSIONS AND IMPACT

By considering these examples and others, it may be possible to develop a process of "cultivating cohorts" in ongoing RCTs, observational cohort studies, and practice settings like HMOs that have strong features of study design. Such an effort could produce sources of data and specimens to reliably answer questions about the use of molecular markers in diagnosis, prognosis, and response to therapy.

Tailoring colorectal cancer screening by considering risk of advanced proximal neoplasia

BACKGROUND

Quantifying the risk of advanced proximal colorectal neoplasia might allow tailoring of colorectal cancer screening, with colonoscopy for those at high risk and less invasive screening for very low-risk persons.

METHODS

We analyzed findings from 10,124 consecutive adults aged≥50 years who underwent screening colonoscopy to the cecum. We quantified the risk of advanced neoplasia (tubular adenoma≥1 cm, a polyp with villous histology or high-grade dysplasia, or adenocarcinoma) both proximally (cecum to splenic flexure) and distally (descending colon to anus). The prevalence of advanced proximal neoplasia was quantified by age, gender, and distal findings.

RESULTS

The mean (standard deviation) age was 57.5 (6.0) years; 44% were women; 7835 (77%) had no neoplasia, and 1856 (18%) had 1 or more nonadvanced adenomas. Overall, 433 subjects (4.3%) had advanced neoplasia (267 distally, 196 proximally, 30 both), 33 (0.33%) of which were adenocarcinoma (18 distal, 15 proximal). The risk of advanced proximal neoplasia increased with age decade (1.13%, 2.00%, and 5.26%, respectively; P=.001) and was higher in men (relative risk [RR], 1.91; confidence interval [CI], 1.32-2.77). In women aged less than 70 years, the risk was 1.1% overall (vs 2.2% in men; RR, 1.98; CI, 1.42-2.76) and 0.86% in those with no distal neoplasia (vs 1.54% in men; RR, 1.81; CI, 1.20-2.74).

CONCLUSIONS

Risk of advanced proximal neoplasia is a function of age and gender. Women aged less than 60 to 70 years have a very low risk, particularly those with no distal adenoma. Sigmoidoscopy with or without occult blood testing may be sufficient and even preferable for screening these subgroups.

Risk for colorectal cancer in persons with a family history of adenomatous polyps: a systematic review

BACKGROUND

The risk for colorectal cancer (CRC) is unclear for persons who have first-degree relatives with adenomatous polyps (adenomas).

PURPOSE

To determine the validity of studies about this issue.

DATA SOURCES

MEDLINE and Cochrane databases from 1966 through 2011.

STUDY SELECTION

Sequential review of titles, abstracts, and text from retrieved articles.

DATA EXTRACTION

Study objective, study design, and numbers in study groups.

DATA SYNTHESIS

Ten studies were identified that have been used to answer the question, "Does having a first-degree relative with an adenoma increase the risk for CRC?" We determined that they instead answer the question, "Does having a first-degree relative with CRC increase the risk for an adenoma?" We identified 2 additional studies that provide more relevant information. One study showed that the risk for CRC in persons who have first-degree relatives with adenomas is greater than the risk in persons who do not have first-degree relatives with adenomas (2.31% vs. 0.53%; relative risk, 4.36 [95% CI, 1.60 to 10.21]). The other study showed that the risk for CRC or large adenomas (≥1 cm) in persons who have first-degree relatives with large adenomas is greater than the risk in persons whose first-degree relatives do not have adenomas or CRC (8.3% vs. 4.2%; adjusted odds ratio, 2.27 [CI, 1.01 to 5.09]).

LIMITATION

Even the 2 relevant studies have design problems that affect validity and generalizability.

CONCLUSION

Most studies that are cited for the risk for CRC when relatives have adenomas do not address the issue. The 2 studies that do address the issue suggest an increased risk but have important methodological limitations. Properly designed studies are needed to measure the risk and identify the factors that modify it.

Bone-density testing interval and transition to osteoporosis in older women

BACKGROUND

Although bone mineral density (BMD) testing to screen for osteoporosis (BMD T score, -2.50 or lower) is recommended for women 65 years of age or older, there are few data to guide decisions about the interval between BMD tests.

METHODS

We studied 4957 women, 67 years of age or older, with normal BMD (T score at the femoral neck and total hip, -1.00 or higher) or osteopenia (T score, -1.01 to -2.49) and with no history of hip or clinical vertebral fracture or of treatment for osteoporosis, followed prospectively for up to 15 years. The BMD testing interval was defined as the estimated time for 10% of women to make the transition to osteoporosis before having a hip or clinical vertebral fracture, with adjustment for estrogen use and clinical risk factors. Transitions from normal BMD and from three subgroups of osteopenia (mild, moderate, and advanced) were analyzed with the use of parametric cumulative incidence models. Incident hip and clinical vertebral fractures and initiation of treatment with bisphosphonates, calcitonin, or raloxifene were treated as competing risks.

RESULTS

The estimated BMD testing interval was 16.8 years (95% confidence interval [CI], 11.5 to 24.6) for women with normal BMD, 17.3 years (95% CI, 13.9 to 21.5) for women with mild osteopenia, 4.7 years (95% CI, 4.2 to 5.2) for women with moderate osteopenia, and 1.1 years (95% CI, 1.0 to 1.3) for women with advanced osteopenia.

CONCLUSIONS

Our data indicate that osteoporosis would develop in less than 10% of older, postmenopausal women during rescreening intervals of approximately 15 years for women with normal bone density or mild osteopenia, 5 years for women with moderate osteopenia, and 1 year for women with advanced osteopenia. (Funded by the National Institutes of Health.).

A framework for evaluating biomarkers for early detection: validation of biomarker panels for ovarian cancer

A panel of biomarkers may improve predictive performance over individual markers. Although many biomarker panels have been described for ovarian cancer, few studies used prediagnostic samples to assess the potential of the panels for early detection. We conducted a multisite systematic evaluation of biomarker panels using prediagnostic serum samples from the Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) screening trial. Using a nested case-control design, levels of 28 biomarkers were measured laboratory-blinded in 118 serum samples obtained before cancer diagnosis and 951 serum samples from matched controls. Five predictive models, each containing 6 to 8 biomarkers, were evaluated according to a predetermined analysis plan. Three sequential analyses were conducted: blinded validation of previously established models (step 1); simultaneous split-sample discovery and validation of models (step 2); and exploratory discovery of new models (step 3). Sensitivity, specificity, sensitivity at 98% specificity, and AUC were computed for the models and CA125 alone among 67 cases diagnosed within one year of blood draw and 476 matched controls. In step 1, one model showed comparable performance to CA125, with sensitivity, specificity, and AUC at 69.2%, 96.6%, and 0.892, respectively. Remaining models had poorer performance than CA125 alone. In step 2, we observed a similar pattern. In step 3, a model derived from all 28 markers failed to show improvement over CA125. Thus, biomarker panels discovered in diagnostic samples may not validate in prediagnostic samples; utilizing prediagnostic samples for discovery may be helpful in developing validated early detection panels.

Principles of cancer screening: lessons from history and study design issues

Early detection of cancer has held great promise and intuitive appeal in the medical community for well over a century. Its history developed in tandem with that of the periodic health examination, in which any deviations--subtle or glaring--from a clearly demarcated "normal" were to be rooted out, given the underlying hypothesis that diseases develop along progressive linear paths of increasing abnormalities. This model of disease development drove the logical deduction that early detection, by "breaking the chain" of cancer development, must be of benefit to affected individuals. In the latter half of the 20th century, researchers and guidelines organizations began to explicitly challenge the core assumptions underpinning many clinical practices. A move away from intuitive thinking began with the development of evidence-based medicine. One key method developed to explicitly quantify the overall risk-benefit profile of a given procedure was the analytic framework. The shift away from pure deductive reasoning and reliance on personal observation was driven, in part, by a rising awareness of critical biases in cancer screening that can mislead clinicians, including healthy volunteer bias, length-biased sampling, lead-time bias, and overdiagnosis. A new focus on the net balance of both benefits and harms when determining the overall worth of an intervention also arose: it was recognized that the potential downsides of early detection were frequently overlooked or discounted because screening is performed on basically healthy persons and initially involves relatively noninvasive methods. Although still inconsistently applied to early detection programs, policies, and belief systems in the United States, an evidence-based approach is essential to counteract the misleading--even potentially harmful--allure of intuition and individual observation.

Understanding differences in the guidelines for colorectal cancer screening

In this issue of Gastroenterology, the editors present 2 expert perspectives on the colorectal screening guidelines published in the May 2008 issue of the journal.

Sources of bias in specimens for research about molecular markers for cancer

Claims about the diagnostic or prognostic accuracy of markers often prove disappointing when "discrimination" found between cancers versus normals is due to bias, a systematic difference between compared groups. This article describes a framework to help simplify and organize current problems in marker research by focusing on the role of specimens as a source of bias in observational research and using that focus to address problems and improve reliability. The central idea is that the "fundamental comparison" in research about markers (ie, the comparison done to assess whether a marker discriminates) involves two distinct processes that are "connected" by specimens. If subject selection (first process) creates baseline inequality between groups being compared, then laboratory analysis of specimens (second process) may erroneously find positive results. Although both processes are important, subject selection more fundamentally influences the quality of marker research, because it can hardwire bias into all comparisons in a way that cannot be corrected by any refinement in laboratory analysis. An appreciation of the separateness of these two processes-and placing investigators with appropriate expertise in charge of each-may increase the reliability of research about cancer biomarkers.

Proteomics research to discover markers: what can we learn from Netflix?

BACKGROUND

Research in the field of proteomics to discover markers for detection of cancer has produced disappointing results, with few markers gaining US Food and Drug Administration approval, and few claims borne out when subsequently tested in rigorous studies. What is the role of better mathematical or statistical analysis in improving the situation?

CONTENT

This article examines whether a recent successful Netflix-sponsored competition using mathematical analysis to develop a prediction model for movie ratings of individual subscribers can serve to improve studies of markers in the field of proteomics. Netflix developed a database of movie preferences of individual subscribers using a longitudinal cohort research design. Groups of researchers then competed to develop better ways to analyze the data. Against this background, the strengths and weaknesses of research design are reviewed, contrasting the Netflix design with that of studies of biomarkers to detect cancer. Such biomarker studies generally have less-strong design, lower numbers of outcomes, and greater difficulty in even just measuring predictors and outcomes, so the fundamental data that will be used in mathematical analysis tend to be much weaker than in other kinds of research.

CONCLUSIONS

If the fundamental data that will be analyzed are not strong, then better analytic methods have limited use in improving the situation. Recognition of this situation is an important first step toward improving the quality of clinical research about markers to detect cancer.

Protein-based multiplex assays: mock presubmissions to the US Food and Drug Administration

As a part of ongoing efforts of the NCI-FDA Interagency Oncology Task Force subcommittee on molecular diagnostics, members of the Clinical Proteomic Technology Assessment for Cancer program of the National Cancer Institute have submitted 2 protein-based multiplex assay descriptions to the Office of In Vitro Diagnostic Device Evaluation and Safety, US Food and Drug Administration. The objective was to evaluate the analytical measurement criteria and studies needed to validate protein-based multiplex assays. Each submission described a different protein-based platform: a multiplex immunoaffinity mass spectrometry platform for protein quantification, and an immunological array platform quantifying glycoprotein isoforms. Submissions provided a mutually beneficial way for members of the proteomics and regulatory communities to identify the analytical issues that the field should address when developing protein-based multiplex clinical assays.

Analytical validation of protein-based multiplex assays: a workshop report by the NCI-FDA interagency oncology task force on molecular diagnostics

Clinical proteomics has the potential to enable the early detection of cancer through the development of multiplex assays that can inform clinical decisions. However, there has been some uncertainty among translational researchers and developers as to the specific analytical measurement criteria needed to validate protein-based multiplex assays. To begin to address the causes of this uncertainty, a day-long workshop titled "Interagency Oncology Task Force Molecular Diagnostics Workshop" was held in which members of the proteomics and regulatory communities discussed many of the analytical evaluation issues that the field should address in development of protein-based multiplex assays for clinical use. This meeting report explores the issues raised at the workshop and details the recommendations that came out of the day's discussions, such as a workshop summary discussing the analytical evaluation issues that specific proteomic technologies should address when seeking US Food and Drug Administration approval.

The Scientific Foundation for personal genomics: recommendations from a National Institutes of Health-Centers for Disease Control and Prevention multidisciplinary workshop

The increasing availability of personal genomic tests has led to discussions about the validity and utility of such tests and the balance of benefits and harms. A multidisciplinary workshop was convened by the National Institutes of Health and the Centers for Disease Control and Prevention to review the scientific foundation for using personal genomics in risk assessment and disease prevention and to develop recommendations for targeted research. The clinical validity and utility of personal genomics is a moving target with rapidly developing discoveries but little translation research to close the gap between discoveries and health impact. Workshop participants made recommendations in five domains: (1) developing and applying scientific standards for assessing personal genomic tests; (2) developing and applying a multidisciplinary research agenda, including observational studies and clinical trials to fill knowledge gaps in clinical validity and utility; (3) enhancing credible knowledge synthesis and information dissemination to clinicians and consumers; (4) linking scientific findings to evidence-based recommendations for use of personal genomics; and (5) assessing how the concept of personal utility can affect health benefits, costs, and risks by developing appropriate metrics for evaluation. To fulfill the promise of personal genomics, a rigorous multidisciplinary research agenda is needed.

Adverse events after outpatient colonoscopy in the Medicare population

BACKGROUND

Although use of colonoscopy has increased substantially among elderly Medicare beneficiaries, no one has described colonoscopy-related adverse events in a representative sample of Medicare patients.

OBJECTIVE

To determine risk for adverse events after outpatient colonoscopy in elderly patients.

DESIGN

Population-based, matched cohort study.

SETTING

Surveillance, Epidemiology, and End Results cancer registry areas.

PATIENTS

Random 5% sample of Medicare beneficiaries, age 66 to 95 years, who underwent outpatient colonoscopy between 1 July 2001 and 31 October 2005 (n = 53 220), matched with beneficiaries who did not have colonoscopy.

MEASUREMENTS

Medicare claims were used to measure the rate of serious gastrointestinal events (bleeding and perforation), other gastrointestinal events, and cardiovascular events resulting in a hospitalization or emergency department visit within 30 days after colonoscopy compared with matched beneficiaries who did not have colonoscopy. Logistic regression was used to estimate adjusted predictive risks for adverse events and to assess whether these events varied by age, comorbid conditions, or type of colonoscopy.

RESULTS

Persons undergoing colonoscopy had a higher risk for adverse gastrointestinal events than their matched group. Rates of adverse events after colonoscopy increased with age. Patients having polypectomy had higher risk for all adverse events compared with their matched group and with the screening and diagnostic colonoscopy groups. Comorbid conditions increased the risk for adverse events. Patients with a history of stroke, chronic obstructive pulmonary disease, atrial fibrillation, or congestive heart failure had significantly higher risk for serious gastrointestinal events.

LIMITATION

The analysis relied on the diagnosis and procedure codes recorded on the Medicare claims.

CONCLUSION

Risks for adverse events after outpatient colonoscopy among elderly Medicare beneficiaries were low; however, they increased with age with specific comorbid conditions and depending on whether polypectomy was done. These data may inform decisions on whether to perform colonoscopy in persons of advanced age or those with comorbid conditions.

Promises and limitations of biomarkers

In many "omics" fields, extraordinary promises have been made about the ability of biomarkers for detecting early cancer, for predicting prognosis, and for predicting response to therapy. Yet very few markers are brought to clinical practice, and many are not even found to be reproducible. This essay discusses chance and bias as threats to validity that can explain the huge disconnect between promise and product, along with approaches to address those threats.

Assessment of serum proteomics to detect large colon adenomas

A noninvasive blood test that could reliably detect early colorectal cancer or large adenomas would provide an important advance in colon cancer screening. The purpose of this study was to determine whether a serum proteomics assay could discriminate between persons with and without a large (> or =1 cm) colon adenoma. To avoid problems of "bias" that have affected many studies about molecular markers for diagnosis, specimens were obtained from a previously conducted study of colorectal cancer etiology in which bloods had been collected before the presence or absence of neoplasm had been determined by colonoscopy, helping to assure that biases related to differences in sample collection and handling would be avoided. Mass spectra of 65 unblinded serum samples were acquired using a nanoelectrospray ionization source on a QSTAR-XL mass spectrometer. Classification patterns were developed using the ProteomeQuest algorithm, performing measurements twice on each specimen, and then applied to a blinded validation set of 70 specimens. After removing 33 specimens that had discordant results, the "test group" comprised 37 specimens that had never been used in training. Although in the primary analysis, no discrimination was found, a single post hoc analysis, done after hemolyzed specimens had been removed, showed a sensitivity of 78%, a specificity of 53%, and an accuracy of 63% (95% confidence interval, 53-72%). The results of this study, although preliminary, suggest that further study of serum proteomics, in a larger number of appropriate specimens, could be useful. They also highlight the importance of understanding sources of "noise" and "bias" in studies of proteomics assays.