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Objective To investigate the capability of various study designs to determine the sensitivity of a disease screening test. Methods Quantities that can be calculated from these designs were derived and examined for their relationship to true sensitivity (the ability to detect unrecognized disease that would surface clinically in the absence of screening) and overdiagnosis. Results To examine the sensitivity of one test, the single cohort design, in which all participants receive the test, is particularly weak, providing only an upper bound on the true sensitivity, and yields no information about overdiagnosis. A randomized design, with one control arm and participants tested in the other, that includes sufficient post-screening follow-up, allows calculation of bounds on, and an approximation to, true sensitivity and also determination of overdiagnosis. Without follow-up, bounds on the true sensitivity can be calculated. To compare two tests, the single cohort paired design in which all participants receive both tests is precarious. The three arm randomized design with post screening follow-up is preferred, yielding an approximation to the true sensitivity, bounds on the true sensitivity, and the extent of overdiagnosis of each test. Without post screening follow-up, bounds on the true sensitivities can be calculated. When an unscreened control arm is not possible, the two-arm randomized design is recommended. Individual test sensitivities cannot be determined, but with sufficient post-screening follow-up, an order relationship can be established, as can the difference in overdiagnosis between the two tests. [ABSTRACT FROM AUTHOR]

Background: The NLST (National Lung Screening Trial) showed reduced lung cancer mortality in high-risk participants (smoking history of ≥ 30 pack-years) aged 55 to 74 years who were randomly assigned to screening with low-dose computed tomography (LDCT) versus those assigned to chest radiography. An advisory panel recently expressed reservations about Medicare coverage of LDCT screening because of concerns about performance in the Medicare-aged population, which accounted for only 25% of the NLST participants. Objective: To examine the results of the NLST LDCT group by age (Medicare-eligible vs. <65 years). Design: Secondary analysis of a group from a randomized trial (NCT00047385). Setting: 33 U.S. screening centers. Patients: 19 612 participants aged 55 to 64 years (under-65 cohort) and 7110 participants aged 65 to 74 years (65+ cohort) at randomization. Intervention: 3 annual rounds of LDCT screening. Measurements: Demographics, smoking and medical history, screening examination adherence and results, diagnostic follow-up procedures and complications, lung cancer diagnoses, treatment, survival, and mortality. Results: The aggregate false-positive rate was higher in the 65+ cohort than in the under-65 cohort (27.7% vs. 22.0%; P < 0.001). Invasive diagnostic procedures after false-positive screening results were modestly more frequent in the older cohort (3.3% vs. 2.7%; P = 0.039). Complications from invasive procedures were low in both groups (9.8% in the under-65 cohort vs. 8 .5% in the 65+ cohort). Prevalence and positive predictive value (PPV) were higher in the 65+ cohort (PPV, 4.9% vs. 3.0%). Resection rates for screen-detected cancer were similar (75.6% in the under-65 cohort vs. 73.2% in the 65+ cohort). Five-year all-cause survival was lower in the 65+ cohort (55.1% vs. 6 4.1%; P = 0.018). Limitation: The oldest screened patient was aged 76 years. Conclusion: NLST participants aged 65 years or older had a higher rate of false-positive screening results than those younger than 65 years but a higher cancer prevalence and PPV. Screen-detected cancer was treated similarly in the groups. Primary Funding Source: National Institutes of Health. [ABSTRACT FROM AUTHOR]

BACKGROUND The National Lung Screening Trial (NLST), which compared lung cancer screening with low-dose computed tomography (LDCT) versus chest radiography (CXR), demonstrated a statistically significant mortality benefit of LDCT screening. In the current study, the authors performed a post hoc analysis to examine whether the benefit was affected by various baseline factors, including age, sex, and smoking status, and whether it differed by tumor histology. METHODS Lung cancer death rates were computed as events over person-years of observation; the mortality risk ratio (RR) was defined as the lung cancer death rate in the LDCT versus CXR trial arms. Poisson regression was used to test for interactions of sex, age (< 65 years vs ≥ 65 years), and smoking status (current vs former) with trial arm. Mortality RRs were also computed for specific lung cancer histologies. RESULTS The overall mortality RR was 0.92 in men and 0.73 in women, with a P value for interaction of .08. RRs were similar for individuals aged < 65 years versus those aged ≥ 65 years (0.82 vs 0.87), and for current versus former smokers (0.81 vs 0.91). By tumor histology, mortality RRs were 0.75 for adenocarcinoma, 0.71 for all non-small cell lung cancers except squamous, 1.23 for squamous cell carcinoma, and 0.90 for small cell carcinoma. RRs were similar for men and women for nonsquamous non-small cell lung cancers (0.71 and 0.70, respectively); women were found to have lower RRs for small cell and squamous cell carcinoma. CONCLUSIONS A benefit of LDCT did not appear to vary substantially by age or smoking status; there was weak evidence of a differential benefit by sex. A differential benefit across lung cancer histologies may exist. Cancer 2013;119:3976-3983. Published 2013. This article is a U.S. Government work and is in the public domain in the USA. [ABSTRACT FROM AUTHOR]

The concept of early detection of cancer holds great promise and intuitive appeal. However, powerful biases can mislead clinicians when evaluating the efficacy of screening tests by clinical observation alone. Selection bias, lead-time bias, length-biased sampling, and overdiagnosis are counterintuitive concepts with critical implications for early-detection efforts. This article explains these biases and other common confounders in cancer screening. The most direct and reliable way to avoid being led astray by intuitions is through the use of randomized controlled trials. [ABSTRACT FROM AUTHOR]

Objective Many cancer screening trials involve a screening programme of one or more screenings with follow-up after the last screening. Usually a maximum follow-up time is selected in advance. However, during the follow-up period there is an opportunity to report the results of the trial sooner than planned. Early reporting of results from a randomized screening trial is important because obtaining a valid result sooner translates into health benefits reaching the general population sooner. The health benefits are reduction in cancer deaths if screening is found to be beneficial and more screening is recommended, or avoidance of unnecessary biopsies, work-ups and morbidity if screening is not found to be beneficial and the rate of screening drops. Methods Our proposed method for deciding if results from a cancer screening trial should be reported earlier in the follow-up period is based on considerations involving postscreening noise. Postscreening noise (sometimes called dilution) refers to cancer deaths in the follow-up period that could not have been prevented by screening: (1) cancer deaths in the screened group that occurred after the last screening in subjects whose cancers were not detected during the screening program and (2) cancer deaths in the control group that occurred after the time of the last screening and whose cancers would not have been detected during the screening programme had they been randomized to screening (the number of which is unobserved). Because postscreening noise increases with follow-up after the last screening, we propose early reporting at the time during the follow-up period when postscreening noise first starts to overwhelm the estimated effect of screening as measured by a z-statistic. This leads to a confidence interval, adjusted for postscreening noise, that would not change substantially with additional follow-up. Details of the early reporting rule were refined by simulation, which also accounts for multiple looks. Results For the re-analysis of the Health Insurance Plan trial for breast cancer screening and the Mayo Lung Project for lung cancer screening, estimates and confidence intervals for the effect of screening on cancer mortality were similar on early reporting and later. Conclusion The proposed early reporting rule for a cancer screening trial with post-screening follow-up is a promising method for making results from the trial available sooner, which translates into health benefits (reduction in cancer deaths or avoidance of unnecessary morbidity) reaching the population sooner. [ABSTRACT FROM AUTHOR]

Objectives: When evaluating screening for the early detection of cancer, it is important to estimate both harms and benefits. One common harm is a false-positive (FP), which is a positive screening result, perhaps followed by an invasive test, with no cancer detected on the diagnostic work-up or within a specified time period. An important goal is to estimate the risk of at least one FP, which we call the cumulative risk of an FP, if persons took a regimen of various screening tests, as is commonly recommended. The estimation is complicated because the data come from a study in which subjects are offered various screening tests in rounds with some missing tests in most subjects. Previous methods for estimating cumulative risk of FPs with a single type of test are not directly applicable, so a new approach was developed. Methods: The tests were ordered by appearance, where the last test was either the first FP (analogous to a failure time) or the last test taken with no FPs having occurred on that test or previously (analogous to a censoring time). We applied a Kaplan-Meier approach for survival analysis with the innovation that the hazard for a first FP for a given test depends on the type of test and number of previous tests of that type which were taken. Results: The method is illustrated with data from the screening arm of the randomized Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. With an FP defined as a diagnostic work-up in the absence of cancer (or advanced adenoma) within three years, the probability of at least one FP among 14 tests in men was 60.5% with 95% confidence interval of (59.3%, 61.6%). Conclusion: A simple estimate is proposed for the probability of at least one FP if persons took a regimen of multiple screening tests of different types. The methodology is useful for summarizing the burden of multiphasic screening programmes. [ABSTRACT FROM AUTHOR]

Background The field of cancer biomarker development has been evolving rapidly. New developments both in the biologic and statistical realms are providing increasing opportunities for evaluation of markers for both early detection and diagnosis of cancer. Purpose To review the major conceptual and methodological issues in cancer biomarker evaluation, with an emphasis on recent developments in statistical methods together with practical recommendations. Methods We organized this review by type of study: preliminary performance, retrospective performance, prospective performance and cancer screening evaluation. Results For each type of study, we discuss methodologic issues, provide examples and discuss strengths and limitations. Conclusion Preliminary performance studies are useful for quickly winnowing down the number of candidate markers; however their results may not apply to the ultimate target population, asymptomatic subjects. If stored specimens from cohort studies with clinical cancer endpoints are available, retrospective studies provide a quick and valid way to evaluate performance of the markers or changes in the markers prior to the onset of clinical symptoms. Prospective studies have a restricted role because they require large sample sizes, and, if the endpoint is cancer on biopsy, there may be bias due to overdiagnosis. Cancer screening studies require very large sample sizes and long follow-up, but are necessary for evaluating the marker as a trigger of early intervention. [ABSTRACT FROM AUTHOR]

The goal of screening tests for a chronic disease such as cancer is early detection and treatment with a consequent reduction in mortality from the disease. Screening tests, however, might produce false positive and false-negative results. With an increasing number of screening tests, it is clear that the risk of a false-positive screen, a finding with potentially significant emotional, financial, and health costs, also increases. (1998, New England Journal of Medicine 338, 1089–1096), (2000, Journal of the National Cancer Institute 92, 1657–1666), and (2000, Statistics in Medicine 19, 1865–1879) investigated this problem under the somewhat unrealistic assumption that the choice of making the decision to drop out at the kth screen does not depend upon the results of the earlier screens. In this article we obtain sufficient and necessary conditions for their assumption to hold and use one of them to provide a method for testing the validity of the assumption. A new model which does not depend on their assumption is introduced. The maximum likelihood estimator of the cumulative risk of receiving a false-positive screen under the new model is derived and its asymptotic normality is proved. The extension of the new model by incorporating covariate information is also considered. We apply our testing method and the new model to data from the breast cancer screening trial of the Health Insurance Plan of Greater New York. [ABSTRACT FROM AUTHOR]

Background: When evaluating cancer screening it is important to estimate the cumulative risk of false positives from periodic screening. Because the data typically come from studies in which the number of screenings varies by subject, estimation must take into account dropouts. A previous approach to estimate the probability of at least one false positive in n screenings unrealistically assumed that the probability of dropout does not depend on prior false positives. Method: By redefining the random variables, we obviate the unrealistic dropout assumption. We also propose a relatively simple logistic regression and extend estimation to the expected number of false positives in n screenings. Results: We illustrate our methodology using data from women ages 40 to 64 who received up to four annual breast cancer screenings in the Health Insurance Program of Greater New York study, which began in 1963. Covariates were age, time since previous screening, screening number, and whether or not a previous false positive occurred. Defining a false positive as an unnecessary biopsy, the only statistically significant covariate was whether or not a previous false positive occurred. Because the effect of screening number was not statistically significant, extrapolation beyond 4 screenings was reasonable. The estimated mean number of unnecessary biopsies in 10 years per woman screened is .11 with 95% confidence interval of (.10, .12). Defining a false positive as an unnecessary work-up, all the covariates were statistically significant and the estimated mean number of unnecessary work-ups in 4 years per woman screened is .34 with 95% confidence interval (.32, .36). Conclusion: Using data from multiple cancer screenings with dropouts, and allowing dropout to depend on previous history of false positives, we propose a logistic regression model to estimate both the probability of at least one false positive and the expected number of false positives associated with n cancer screenings. The methodology can be used for both informed decision making at the individual level, as well as planning of health services. [ABSTRACT FROM AUTHOR]

Background: Because randomized cancer screening trials are very expensive, observational cancer screening studies can play an important role in the early phases of screening evaluation. Periodic screening evaluation (PSE) is a methodology for estimating the reduction in population cancer mortality from data on subjects who receive regularly scheduled screens. Although PSE does not require assumptions about natural history of cancer it requires other assumptions, particularly progressive detection -- the assumption that once a cancer is detected by a screening test, it will always be detected by the screening test. Methods: We formulate a simple version of PSE and show that it leads to an upper bound on screening efficacy if the progressive detection assumption does not hold (and any effect of birth cohort is minimal) To determine if the upper bound is reasonable, for three randomized screening trials, we compared PSE estimates based only on screened subjects with PSE estimates based on all subjects. Results: In the three randomized screening trials, PSE estimates based on screened subjects gave fairly close results to PSE estimates based on all subjects. Conclusion: PSE has promise for obtaining an upper bound on the reduction in population cancer mortality rates based on observational screening data. If the upper bound estimate is found to be small and any birth cohort effects are likely minimal, then a definitive randomized trial would not be warranted. [ABSTRACT FROM AUTHOR]

Background: If intervention A bests B in one randomized trial, and B bests C in another randomized trial, can one conclude that A is better than C? The problem was motivated by the planning of a randomized trial, where A is spiral-CT screening, B is x-ray screening, and C is no screening. On its surface, this would appear to be a straightforward application of the transitive principle of logic. Methods: We extended the graphical approach for omitted binary variables that was originally developed to illustrate Simpson's paradox, applying it to hypothetical, but plausible scenarios involving lung cancer screening, treatment for gastric cancer, and antibiotic therapy for clinical pneumonia. Results: Graphical illustrations of the three examples show different ways the transitive fallacy for randomized trials can arise due to changes in an unobserved or unadjusted binary variable. In the most dramatic scenario, B bests C in the first trial, A bests B in the second trial, but C bests A at the time of the second trial. Conclusion: Even with large sample sizes, combining results from a previous randomized trial of B versus C with results from a new randomized trial of A versus B will not guarantee correct inference about A versus C. A three-arm trial of A, B, and C would protect against this problem and should be considered when the sequential trials are performed in the context of changing secular trends in important omitted variables such as therapy in cancer screening trials. [ABSTRACT FROM AUTHOR]

Background: The evaluation of randomized trials for cancer screening involves special statistical considerations not found in therapeutic trials. Although some of these issues have been discussed previously, we present important recent and new methodologies. Methods: Our emphasis is on simple approaches. Results: We make the following recommendations: (1) Use death from cancer as the primary endpoint, but review death records carefully and report all causes of death (2) Use a simple "causal" estimate to adjust for nonattendance and contamination occurring immediately after randomization (3) Use a simple adaptive estimate to adjust for dilution in follow-up after the last screen Conclusion: The proposed guidelines combine recent methodological work on screening endpoints and noncompliance/contamination with a new adaptive method to adjust for dilution in a study where follow-up continues after the last screen. These guidelines ensure good practice in the design and analysis of randomized trials of cancer screening. [ABSTRACT FROM AUTHOR]

Focuses on a study which evaluated the evidence for recommending the screening of asymptomatic men for prostate cancer with blood test to detect a prostate specific antigen. History and development of the prostate-specific antigen assay; Uncertainties about the efficacy of the prostate-specific antigen assay as a screening tool for cancer; Potential harm of mass screening assays for prostate-specific antigen.

The author reflects on the study of National Lung Screening Trial (NLST) launched in September 2002 by U.S. National Cancer Institute (NCI). The author stated that subsequent calls were there for routine lung cancer screening without further proof and it was also assumed that it would be highly cost-effective in terms of saved life years. It was also suggested that it was unethical with positive single arm studies.

Elaborates the different aspects of cancer screening from the perspective of behavioral science. Approaches on general population screening; Complexities of genetic screening.

The authors comment on the use of statistical models to determine the pros and cons of using mammography screening. They examine the complex statistical microsimulation models used in a study that determined the balance of benefits and harms of routine screening mammography. They also describe major components of uncertainty that apply to forecasting models.

The author discusses the study conducted by Pace et al. on breast cancer screening's risks and benefits through mammography. Tackled are the guidelines released in the U.S. for breast cancer prevention and management for women. The significance of a balanced messaging on women's ability in decision-making process is noted.

The article reports on the public health importance of the development of an effective lung cancer prevention tool for lung cancer screening. The Mayo lung project (MLP) was a randomized screening trial of chest x-ray and pooled sputum cytology every four months against usual care. Moreover, the MLP was designed to have a 90 percent power to detect a 50 percent reduction in lung cancer mortality.

The article provides information on extensive screening in the U.S. for prostate cancer with prostate-specific antigen (PSA). The article provides information on effective division of medical community and European Randomized Study of Screening for Prostate Cancer (ERSPC), deaths from prostate cancer, and screening phase.

Background: The goal of screening mammography is to detect small malignant tumors before they grow large enough to cause symptoms. Effective screening should therefore lead to the detection of a greater number of small tumors, followed by fewer large tumors over time.Methods: We used data from the Surveillance, Epidemiology, and End Results (SEER) program, 1975 through 2012, to calculate the tumor-size distribution and size-specific incidence of breast cancer among women 40 years of age or older. We then calculated the size-specific cancer case fatality rate for two time periods: a baseline period before the implementation of widespread screening mammography (1975 through 1979) and a period encompassing the most recent years for which 10 years of follow-up data were available (2000 through 2002).Results: After the advent of screening mammography, the proportion of detected breast tumors that were small (invasive tumors measuring <2 cm or in situ carcinomas) increased from 36% to 68%; the proportion of detected tumors that were large (invasive tumors measuring ≥2 cm) decreased from 64% to 32%. However, this trend was less the result of a substantial decrease in the incidence of large tumors (with 30 fewer cases of cancer observed per 100,000 women in the period after the advent of screening than in the period before screening) and more the result of a substantial increase in the detection of small tumors (with 162 more cases of cancer observed per 100,000 women). Assuming that the underlying disease burden was stable, only 30 of the 162 additional small tumors per 100,000 women that were diagnosed were expected to progress to become large, which implied that the remaining 132 cases of cancer per 100,000 women were overdiagnosed (i.e., cases of cancer were detected on screening that never would have led to clinical symptoms). The potential of screening to lower breast cancer mortality is reflected in the declining incidence of larger tumors. However, with respect to only these large tumors, the decline in the size-specific case fatality rate suggests that improved treatment was responsible for at least two thirds of the reduction in breast cancer mortality.Conclusions: Although the rate of detection of large tumors fell after the introduction of screening mammography, the more favorable size distribution was primarily the result of the additional detection of small tumors. Women were more likely to have breast cancer that was overdiagnosed than to have earlier detection of a tumor that was destined to become large. The reduction in breast cancer mortality after the implementation of screening mammography was predominantly the result of improved systemic therapy. [ABSTRACT FROM AUTHOR]

Background: Annual low-dose CT screening for lung cancer has been recommended for high-risk individuals, but the necessity of yearly low-dose CT in all eligible individuals is uncertain. This study examined rates of lung cancer in National Lung Screening Trial (NLST) participants who had a negative prevalence (initial) low-dose CT screen to explore whether less frequent screening could be justified in some lower-risk subpopulations.Methods: We did a retrospective cohort analysis of data from the NLST, a randomised, multicentre screening trial comparing three annual low-dose CT assessments with three annual chest radiographs for the early detection of lung cancer in high-risk, eligible individuals (aged 55-74 years with at least a 30 pack-year history of cigarette smoking, and, if a former smoker, had quit within the past 15 years), recruited from US medical centres between Aug 5, 2002, and April 26, 2004. Participants were followed up for up to 5 years after their last annual screen. For the purposes of this analysis, our cohort consisted of all NLST participants who had received a low-dose CT prevalence (T0) screen. We determined the frequency, stage, histology, study year of diagnosis, and incidence of lung cancer, as well as overall and lung cancer-specific mortality, and whether lung cancers were detected as a result of screening or within 1 year of a negative screen. We also estimated the effect on mortality if the first annual (T1) screen in participants with a negative T0 screen had not been done. The NLST is registered with ClinicalTrials.gov, number NCT00047385.Findings: Our cohort consisted of 26 231 participants assigned to the low-dose CT screening group who had undergone their T0 screen. The 19 066 participants with a negative T0 screen had a lower incidence of lung cancer than did all 26 231 T0-screened participants (371·88 [95% CI 337·97-408·26] per 100 000 person-years vs 661·23 [622·07-702·21]) and had lower lung cancer-related mortality (185·82 [95% CI 162·17-211·93] per 100 000 person-years vs 277·20 [252·28-303·90]). The yield of lung cancer at the T1 screen among participants with a negative T0 screen was 0·34% (62 screen-detected cancers out of 18 121 screened participants), compared with a yield at the T0 screen among all T0-screened participants of 1·0% (267 of 26 231). We estimated that if the T1 screen had not been done in the T0 negative group, at most, an additional 28 participants in the T0 negative group would have died from lung cancer (a rise in mortality from 185·82 [95% CI 162·17-211·93] per 100 000 person-years to 212·14 [186·80-239·96]) over the course of the trial.Interpretation: Participants with a negative low-dose CT prevalence screen had a lower incidence of lung cancer and lung cancer-specific mortality than did all participants who underwent a prevalence screen. Because overly frequent screening has associated harms, increasing the interval between screens in participants with a negative low-dose CT prevalence screen might be warranted.Funding: None. [ABSTRACT FROM AUTHOR]

Background: The effect of screening with prostate-specific–antigen (PSA) testing and digital rectal examination on the rate of death from prostate cancer is unknown. This is the first report from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial on prostate-cancer mortality. Methods: From 1993 through 2001, we randomly assigned 76,693 men at 10 U.S. study centers to receive either annual screening (38,343 subjects) or usual care as the control (38,350 subjects). Men in the screening group were offered annual PSA testing for 6 years and digital rectal examination for 4 years. The subjects and health care providers received the results and decided on the type of follow-up evaluation. Usual care sometimes included screening, as some organizations have recommended. The numbers of all cancers and deaths and causes of death were ascertained. Results: In the screening group, rates of compliance were 85% for PSA testing and 86% for digital rectal examination. Rates of screening in the control group increased from 40% in the first year to 52% in the sixth year for PSA testing and ranged from 41 to 46% for digital rectal examination. After 7 years of follow-up, the incidence of prostate cancer per 10,000 person-years was 116 (2820 cancers) in the screening group and 95 (2322 cancers) in the control group (rate ratio, 1.22; 95% confidence interval [CI], 1.16 to 1.29). The incidence of death per 10,000 person-years was 2.0 (50 deaths) in the screening group and 1.7 (44 deaths) in the control group (rate ratio, 1.13; 95% CI, 0.75 to 1.70). The data at 10 years were 67% complete and consistent with these overall findings. Conclusions: After 7 to 10 years of follow-up, the rate of death from prostate cancer was very low and did not differ significantly between the two study groups. (ClinicalTrials.gov number, NCT00002540.) N Engl J Med 2009;360:1310-9. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article "Breast-cancer tumor size, overdiagnosis, and mammography screening effectiveness" by H. Gilbert Welch and colleagues which appeared in the October 13, 2016 issue.