David F. Ransohoff

Risk of advanced proximal neoplasms in asymptomatic adults according to the distal colorectal findings

BACKGROUND AND METHODS The clinical significance of a distal colorectal polyp is uncertain. We determined the risk of advanced proximal neoplasia, defined as a polyp with villous features, a polyp with high-grade dysplasia, or cancer, among persons with distal hyperplastic or neoplastic polyps as compared with the risk among persons with no distal polyps. We analyzed data from 1994 consecutive asymptomatic adults (age, 50 years or older) who underwent colonoscopic screening for the first time between September 1995 and December 1998 as part of a program sponsored by an employer. The location and histologic features of all polyps were recorded. Colonoscopy to the level of the cecum was completed in 97.0 percent of the patients. RESULTS Sixty-one patients (3.1 percent) had advanced lesions in the distal colon, including 5 with cancer, and 50 (2.5 percent) had advanced proximal lesions, including 7 with cancer. Twenty-three patients with advanced proximal neoplasms (46 percent) had no distal polyps. The prevalence of advanced proximal neoplasia among patients with no distal polyps was 1.5 percent (23 cases among 1564 persons; 95 percent confidence interval, 0.9 to 2.1 percent). Among patients with distal hyperplastic polyps, those with distal tubular adenomas, and those with advanced distal polyps, the prevalence of advanced proximal neoplasia was 4.0 percent (8 cases among 201 patients), 7.1 percent (12 cases among 168 patients), and 11.5 percent (7 cases among 61 patients), respectively. The relative risk of advanced proximal neoplasia, adjusted for age and sex, was 2.6 for patients with distal hyperplastic polyps, 4.0 for those with distal tubular adenomas, and 6.7 for those with advanced distal polyps, as compared with patients who had no distal polyps. Older age and male sex were associated with an increased risk of advanced proximal neoplasia (relative risk, 1.3 for every five years of age and 3.3 for male sex). CONCLUSIONS Asymptomatic persons 50 years of age or older who have polyps in the distal colon are more likely to have advanced proximal neoplasia than are persons without distal polyps. However, if colonoscopic screening is performed only in persons with distal polyps, about half the cases of advanced proximal neoplasia will not be detected.

Multi-site assessment of the precision and reproducibility of multiple reaction monitoring-based measurements of proteins in plasma.

Verification of candidate biomarkers relies upon specific, quantitative assays optimized for selective detection of target proteins, and is increasingly viewed as a critical step in the discovery pipeline that bridges unbiased biomarker discovery to preclinical validation. Although individual laboratories have demonstrated that multiple reaction monitoring (MRM) coupled with isotope dilution mass spectrometry can quantify candidate protein biomarkers in plasma, reproducibility and transferability of these assays between laboratories have not been demonstrated. We describe a multilaboratory study to assess reproducibility, recovery, linear dynamic range and limits of detection and quantification of multiplexed, MRM-based assays, conducted by NCI-CPTAC. Using common materials and standardized protocols, we demonstrate that these assays can be highly reproducible within and across laboratories and instrument platforms, and are sensitive to low μg/ml protein concentrations in unfractionated plasma. We provide data and benchmarks against which individual laboratories can compare their performance and evaluate new technologies for biomarker verification in plasma.

Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration.

In medicine, numerous decisions are made by care providers, often in shared decision making, on the basis of an estimated probability that a specific disease or condition is present (diagnostic setting) or a specific event will occur in the future (prognostic setting) in an individual. In the diagnostic setting, the probability that a particular disease is present can be used, for example, to inform the referral of patients for further testing, to initiate treatment directly, or to reassure patients that a serious cause for their symptoms is unlikely. In the prognostic context, predictions can be used for planning lifestyle or therapeutic decisions on the basis of the risk for developing a particular outcome or state of health within a specific period (13). Such estimates of risk can also be used to risk-stratify participants in therapeutic intervention trials (47). In both the diagnostic and prognostic setting, probability estimates are commonly based on combining information from multiple predictors observed or measured from an individual (1, 2, 810). Information from a single predictor is often insufficient to provide reliable estimates of diagnostic or prognostic probabilities or risks (8, 11). In virtually all medical domains, diagnostic and prognostic multivariable (risk) prediction models are being developed, validated, updated, and implemented with the aim to assist doctors and individuals in estimating probabilities and potentially influence their decision making. A multivariable prediction model is a mathematical equation that relates multiple predictors for a particular individual to the probability of or risk for the presence (diagnosis) or future occurrence (prognosis) of a particular outcome (10, 12). Other names for a prediction model include risk prediction model, predictive model, prognostic (or prediction) index or rule, and risk score (9). Predictors are also referred to as covariates, risk indicators, prognostic factors, determinants, test results, ormore statisticallyindependent variables. They may range from demographic characteristics (for example, age and sex), medical historytaking, and physical examination results to results from imaging, electrophysiology, blood and urine measurements, pathologic examinations, and disease stages or characteristics, or results from genomics, proteomics, transcriptomics, pharmacogenomics, metabolomics, and other new biological measurement platforms that continuously emerge. Diagnostic and Prognostic Prediction Models Multivariable prediction models fall into 2 broad categories: diagnostic and prognostic prediction models (Box A). In a diagnostic model, multiplethat is, 2 or morepredictors (often referred to as diagnostic test results) are combined to estimate the probability that a certain condition or disease is present (or absent) at the moment of prediction (Box B). They are developed from and to be used for individuals suspected of having that condition. Box A. Schematic representation of diagnostic and prognostic prediction modeling studies. The nature of the prediction in diagnosis is estimating the probability that a specific outcome or disease is present (or absent) within an individual, at this point in timethat is, the moment of prediction (T= 0). In prognosis, the prediction is about whether an individual will experience a specific event or outcome within a certain time period. In other words, in diagnostic prediction the interest is in principle a cross-sectional relationship, whereas prognostic prediction involves a longitudinal relationship. Nevertheless, in diagnostic modeling studies, for logistical reasons, a time window between predictor (index test) measurement and the reference standard is often necessary. Ideally, this interval should be as short as possible without starting any treatment within this period. Box B. Similarities and differences between diagnostic and prognostic prediction models. In a prognostic model, multiple predictors are combined to estimate the probability of a particular outcome or event (for example, mortality, disease recurrence, complication, or therapy response) occurring in a certain period in the future. This period may range from hours (for example, predicting postoperative complications [13]) to weeks or months (for example, predicting 30-day mortality after cardiac surgery [14]) or years (for example, predicting the 5-year risk for developing type 2 diabetes [15]). Prognostic models are developed and are to be used in individuals at risk for developing that outcome. They may be models for either ill or healthy individuals. For example, prognostic models include models to predict recurrence, complications, or death in a certain period after being diagnosed with a particular disease. But they may also include models for predicting the occurrence of an outcome in a certain period in individuals without a specific disease: for example, models to predict the risk for developing type 2 diabetes (16) or cardiovascular events in middle-aged nondiseased individuals (17), or the risk for preeclampsia in pregnant women (18). We thus use prognostic in the broad sense, referring to the prediction of an outcome in the future in individuals at risk for that outcome, rather than the narrower definition of predicting the course of patients who have a particular disease with or without treatment (1). The main difference between a diagnostic and prognostic prediction model is the concept of time. Diagnostic modeling studies are usually cross-sectional, whereas prognostic modeling studies are usually longitudinal. In this document, we refer to both diagnostic and prognostic prediction models as prediction models, highlighting issues that are specific to either type of model. Development, Validation, and Updating of Prediction Models Prediction model studies may address the development of a new prediction model (10), a model evaluation (often referred to as model validation) with or without updating of the model [1921]), or a combination of these (Box C and Figure 1). Box C. Types of prediction model studies. Figure 1. Types of prediction model studies covered by the TRIPOD statement. D = development data; V = validation data. Model development studies aim to derive a prediction model by selecting predictors and combining them into a multivariable model. Logistic regression is commonly used for cross-sectional (diagnostic) and short-term (for example 30-day mortality) prognostic outcomes and Cox regression for long-term (for example, 10-year risk) prognostic outcomes. Studies may also focus on quantifying the incremental or added predictive value of a specific predictor (for example, newly discovered) (22) to a prediction model. Quantifying the predictive ability of a model on the same data from which the model was developed (often referred to as apparent performance [Figure 1]) will tend to give an optimistic estimate of performance, owing to overfitting (too few outcome events relative to the number of candidate predictors) and the use of predictor selection strategies (2325). Studies developing new prediction models should therefore always include some form of internal validation to quantify any optimism in the predictive performance (for example, calibration and discrimination) of the developed model and adjust the model for overfitting. Internal validation techniques use only the original study sample and include such methods as bootstrapping or cross-validation. Internal validation is a necessary part of model development (2). After developing a prediction model, it is strongly recommended to evaluate the performance of the model in other participant data than was used for the model development. External validation (Box C and Figure 1) (20, 26) requires that for each individual in the new participant data set, outcome predictions are made using the original model (that is, the published model or regression formula) and compared with the observed outcomes. External validation may use participant data collected by the same investigators, typically using the same predictor and outcome definitions and measurements, but sampled from a later period (temporal or narrow validation); by other investigators in another hospital or country (though disappointingly rare [27]), sometimes using different definitions and measurements (geographic or broad validation); in similar participants, but from an intentionally different setting (for example, a model developed in secondary care and assessed in similar participants, but selected from primary care); or even in other types of participants (for example, model developed in adults and assessed in children, or developed for predicting fatal events and assessed for predicting nonfatal events) (19, 20, 26, 2830). In case of poor performance (for example, systematic miscalibration), when evaluated in an external validation data set, the model can be updated or adjusted (for example, recalibrating or adding a new predictor) on the basis of the validation data set (Box C) (2, 20, 21, 31). Randomly splitting a single data set into model development and model validation data sets is frequently done to develop and validate a prediction model; this is often, yet erroneously, believed to be a form of external validation. However, this approach is a weak and inefficient form of internal validation, because not all available data are used to develop the model (23, 32). If the available development data set is sufficiently large, splitting by time and developing a model using data from one period and evaluating its performance using the data from the other period (temporal validation) is a stronger approach. With a single data set, temporal splitting and model validation can be considered intermediate between internal and external validation. Incomplete and Inaccurate Reporting Prediction models are becoming increasingly abundant in the medical literature (9, 33, 34), and policymakers are incre

Multitarget Stool DNA Testing for Colorectal-Cancer Screening

BACKGROUND An accurate, noninvasive test could improve the effectiveness of colorectal-cancer screening. METHODS We compared a noninvasive, multitarget stool DNA test with a fecal immunochemical test (FIT) in persons at average risk for colorectal cancer. The DNA test includes quantitative molecular assays for KRAS mutations, aberrant NDRG4 and BMP3 methylation, and β-actin, plus a hemoglobin immunoassay. Results were generated with the use of a logistic-regression algorithm, with values of 183 or more considered to be positive. FIT values of more than 100 ng of hemoglobin per milliliter of buffer were considered to be positive. Tests were processed independently of colonoscopic findings. RESULTS Of the 9989 participants who could be evaluated, 65 (0.7%) had colorectal cancer and 757 (7.6%) had advanced precancerous lesions (advanced adenomas or sessile serrated polyps measuring ≥1 cm in the greatest dimension) on colonoscopy. The sensitivity for detecting colorectal cancer was 92.3% with DNA testing and 73.8% with FIT (P=0.002). The sensitivity for detecting advanced precancerous lesions was 42.4% with DNA testing and 23.8% with FIT (P<0.001). The rate of detection of polyps with high-grade dysplasia was 69.2% with DNA testing and 46.2% with FIT (P=0.004); the rates of detection of serrated sessile polyps measuring 1 cm or more were 42.4% and 5.1%, respectively (P<0.001). Specificities with DNA testing and FIT were 86.6% and 94.9%, respectively, among participants with nonadvanced or negative findings (P<0.001) and 89.8% and 96.4%, respectively, among those with negative results on colonoscopy (P<0.001). The numbers of persons who would need to be screened to detect one cancer were 154 with colonoscopy, 166 with DNA testing, and 208 with FIT. CONCLUSIONS In asymptomatic persons at average risk for colorectal cancer, multitarget stool DNA testing detected significantly more cancers than did FIT but had more false positive results. (Funded by Exact Sciences; ClinicalTrials.gov number, NCT01397747.).

Proteogenomic characterization of human colon and rectal cancer

Extensive genomic characterization of human cancers presents the problem of inference from genomic abnormalities to cancer phenotypes. To address this problem, we analysed proteomes of colon and rectal tumours characterized previously by The Cancer Genome Atlas (TCGA) and perform integrated proteogenomic analyses. Somatic variants displayed reduced protein abundance compared to germline variants. Messenger RNA transcript abundance did not reliably predict protein abundance differences between tumours. Proteomics identified five proteomic subtypes in the TCGA cohort, two of which overlapped with the TCGA ‘microsatellite instability/CpG island methylation phenotype’ transcriptomic subtype, but had distinct mutation, methylation and protein expression patterns associated with different clinical outcomes. Although copy number alterations showed strong cis- and trans-effects on mRNA abundance, relatively few of these extend to the protein level. Thus, proteomics data enabled prioritization of candidate driver genes. The chromosome 20q amplicon was associated with the largest global changes at both mRNA and protein levels; proteomics data highlighted potential 20q candidates, including HNF4A (hepatocyte nuclear factor 4, alpha), TOMM34 (translocase of outer mitochondrial membrane 34) and SRC (SRC proto-oncogene, non-receptor tyrosine kinase). Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords a new paradigm for understanding cancer biology.

The natural history of silent gallstones: the innocent gallstone is not a myth.

ABOUT 15 million Americans have gallstones.1 A majority of these gallstones are silent (painless).2 , 3 Should silent gallstones be treated prophylactically or left alone? The answer depends in par...

RESULTS OF SCREENING COLONOSCOPY AMONG PERSONS 40 TO 49 YEARS OF AGE

BACKGROUND The prevalence of colorectal lesions in persons 40 to 49 years of age, as identified on colonoscopy, has not been determined. METHODS We reviewed the procedure and pathology reports for 906 consecutive persons 40 to 49 years of age who voluntarily participated in an employer-based screening-colonoscopy program. The histologic features of lesions that were identified and removed on endoscopy were categorized according to those of the most advanced lesion removed proximally (up to the junction of the splenic flexure and the descending colon) and the most advanced lesion removed distally. An advanced lesion was defined as an adenoma at least 1 cm in diameter, a polyp with villous histologic features or severe dysplasia, or a cancer. RESULTS Among those who underwent colonoscopic screening, 78.9 percent had no detected lesions, 10.0 percent had hyperplastic polyps, 8.7 percent had tubular adenomas, and 3.5 percent had advanced neoplasms, none of which were cancerous (95 percent confidence interval for cancer, 0 to 0.4 percent). Eighteen of 33 advanced neoplasms (55 percent) were located distally and were potentially within reach of a sigmoidoscope. If these results are applicable to the general population, at least 250 persons, and perhaps 1000 or more, would need to be screened to detect one cancer in this age group. CONCLUSIONS Colonoscopic detection of colorectal cancer is uncommon in asymptomatic persons 40 to 49 years of age. The noncancerous lesions are equally distributed proximally and distally. The low yield of screening colonoscopy in this age group is consistent with current recommendations about the age at which to begin screening in persons at average risk.

Prospective evaluation of methylated SEPT9 in plasma for detection of asymptomatic colorectal cancer

Background As screening methods for colorectal cancer (CRC) are limited by uptake and adherence, further options are sought. A blood test might increase both, but none has yet been tested in a screening setting. Objective We prospectively assessed the accuracy of circulating methylated SEPT9 DNA (mSEPT9) for detecting CRC in a screening population. Design Asymptomatic individuals ≥50 years old scheduled for screening colonoscopy at 32 US and German clinics voluntarily gave blood plasma samples before colon preparation. Using a commercially available assay, three independent blinded laboratories assayed plasma DNA of all CRC cases and a stratified random sample of other subjects in duplicate real time PCRs. The primary outcomes measures were standardised for overall sensitivity and specificity estimates. Results 7941 men (45%) and women (55%), mean age 60 years, enrolled. Results from 53 CRC cases and from 1457 subjects without CRC yielded a standardised sensitivity of 48.2% (95% CI 32.4% to 63.6%; crude rate 50.9%); for CRC stages I–IV, values were 35.0%, 63.0%, 46.0% and 77.4%, respectively. Specificity was 91.5% (95% CI 89.7% to 93.1%; crude rate 91.4%). Sensitivity for advanced adenomas was low (11.2%). Conclusions Our study using the blood based mSEPT9 test showed that CRC signal in blood can be detected in asymptomatic average risk individuals undergoing screening. However, the utility of the test for population screening for CRC will require improved sensitivity for detection of early cancers and advanced adenomas. Clinical Trial Registration Number: NCT00855348

Addressing overdiagnosis and overtreatment in cancer: a prescription for change

A vast range of disorders--from indolent to fast-growing lesions--are labelled as cancer. Therefore, we believe that several changes should be made to the approach to cancer screening and care, such as use of new terminology for indolent and precancerous disorders. We propose the term indolent lesion of epithelial origin, or IDLE, for those lesions (currently labelled as cancers) and their precursors that are unlikely to cause harm if they are left untreated. Furthermore, precursors of cancer or high-risk disorders should not have the term cancer in them. The rationale for this change in approach is that indolent lesions with low malignant potential are common, and screening brings indolent lesions and their precursors to clinical attention, which leads to overdiagnosis and, if unrecognised, possible overtreatment. To minimise that potential, new strategies should be adopted to better define and manage IDLEs. Screening guidelines should be revised to lower the chance of detection of minimal-risk IDLEs and inconsequential cancers with the same energy traditionally used to increase the sensitivity of screening tests. Changing the terminology for some of the lesions currently referred to as cancer will allow physicians to shift medicolegal notions and perceived risk to reflect the evolving understanding of biology, be more judicious about when a biopsy should be done, and organise studies and registries that offer observation or less invasive approaches for indolent disease. Emphasis on avoidance of harm while assuring benefit will improve screening and treatment of patients and will be equally effective in the prevention of death from cancer.

Screening for Colorectal Cancer

A healthy 50-year-old woman with no risk factors for colorectal cancer other than age comes in for an annual examination. Which screening test for colorectal cancer should be recommended?