Background The optimal screening policy for lung cancer is unknown. Objective To identify efficient CT-screening scenarios where relatively more lung cancer deaths are averted for fewer CT screens. Design Comparative modeling study using 5 independent models. Data Sources The National Lung Screening Trial, the Prostate, Lung, Colorectal and Ovarian trial, the Surveillance, Epidemiology, and End Results program, and U.S. Smoking History Generator. Target Population U.S. cohort born in 1950. Time Horizon Cohort followed from ages 45 to 90. Perspective Societal. Intervention 576 scenarios with varying eligibility criteria (age, smoking pack-years, years quit) and screening intervals. Outcome Measures Benefits: lung cancer deaths averted or life-years gained; harms: CT-exams, false positives (including biopsy/surgery), overdiagnosed cases, radiation-related deaths. Results of Best-Case Annual screening from age 55 through 80 for ever-smokers with at least 30 pack-years and ex-smokers with less than 15 years since quitting was the most advantageous strategy. It would lead to 50% (45 to 54%) of cancers being detected at an early stage (I/II); 575 screens per lung cancer death averted; a 14% (8.2 to 23.5%) lung cancer mortality reduction; 497 lung cancer deaths averted; and 5,250 life-years gained per the 100,000-member cohort. Harms would include 67,550 false-positive tests, 910 biopsies or surgeries for benign lesions and 190 overdiagnosed cancers (3.7%; 1.4 to 8.3%). Results of Sensitivity Analysis The number of cancer deaths averted for the scenario varied across models between 177 and 862, and for overdiagnosed cancers between 72 and 426. Limitations Scenarios assumed 100% screening adherence. Data derived from trials with short duration were extrapolated to life-time follow-up. Conclusion Annual CT screening for lung cancer has a favorable benefit-harm ratio for individuals aged 55 through 80 years with 30 or more pack-year exposure to smoking.
IMPORTANCE The US Preventive Services Task Force (USPSTF) is updating its 2013 lung cancer screening guidelines, which recommend annual screening for adults aged 55 through 80 years who have a smoking history of at least 30 pack-years and currently smoke or have quit within the past 15 years. OBJECTIVE To inform the USPSTF guidelines by estimating the benefits and harms associated with various low-dose computed tomography (LDCT) screening strategies. DESIGN, SETTING, AND PARTICIPANTS Comparative simulation modeling with 4 lung cancer natural history models for individuals from the 1950 and 1960 US birth cohorts who were followed up from aged 45 through 90 years. EXPOSURES Screening with varying starting ages, stopping ages, and screening frequency. Eligibility criteria based on age, cumulative pack-years, and years since quitting smoking (risk factor-based) or on age and individual lung cancer risk estimation using risk prediction models with varying eligibility thresholds (risk model-based). A total of 1092 LDCT screening strategies were modeled. Full uptake and adherence were assumed for all scenarios. MAIN OUTCOMES AND MEASURES Estimated lung cancer deaths averted and life-years gained (benefits) compared with no screening. Estimated lifetime number of LDCT screenings, false-positive results, biopsies, overdiagnosed cases, and radiation-related lung cancer deaths (harms). RESULTS Efficient screening programs estimated to yield the most benefits for a given number of screenings were identified. Most of the efficient risk factor-based strategies started screening at aged 50 or 55 years and stopped at aged 80 years. The 2013 USPSTF-recommended criteria were not among the efficient strategies for the 1960 US birth cohort. Annual strategies with a minimum criterion of 20 pack-years of smoking were efficient and, compared with the 2013 USPSTF-recommended criteria, were estimated to increase screening eligibility (20.6%-23.6% vs 14.1% of the population ever eligible), lung cancer deaths averted (469-558 per 100 000 vs 381 per 100 000), and life-years gained (6018-7596 per 100 000 vs 4882 per 100 000). However, these strategies were estimated to result in more false-positive test results (1.9-2.5 per person screened vs 1.9 per person screened with the USPSTF strategy), overdiagnosed lung cancer cases (83-94 per 100 000 vs 69 per 100 000), and radiation-related lung cancer deaths (29.0-42.5 per 100 000 vs 20.6 per 100 000). Risk model-based vs risk factor-based strategies were estimated to be associated with more benefits and fewer radiation-related deaths but more overdiagnosed cases. CONCLUSIONS AND RELEVANCE Microsimulation modeling studies suggested that LDCT screening for lung cancer compared with no screening may increase lung cancer deaths averted and life-years gained when optimally targeted and implemented. Screening individuals at aged 50 or 55 years through aged 80 years with 20 pack-years or more of smoking exposure was estimated to result in more benefits than the 2013 USPSTF-recommended criteria and less ...
Key Points This study is a retrospective analysis of long-term outcomes of patients with FL treated at Stanford University for 4 decades. Study results showed significant improvement in OS in patients with FL despite no change in event-free survival after first-line therapy.
BackgroundSelection of candidates for lung cancer screening based on individual risk has been proposed as an alternative to criteria based on age and cumulative smoking exposure (pack-years). Nine previously established risk models were assessed for their ability to identify those most likely to develop or die from lung cancer. All models considered age and various aspects of smoking exposure (smoking status, smoking duration, cigarettes per day, pack-years smoked, time since smoking cessation) as risk predictors. In addition, some models considered factors such as gender, race, ethnicity, education, body mass index, chronic obstructive pulmonary disease, emphysema, personal history of cancer, personal history of pneumonia, and family history of lung cancer.Methods and findingsRetrospective analyses were performed on 53,452 National Lung Screening Trial (NLST) participants (1,925 lung cancer cases and 884 lung cancer deaths) and 80,672 Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO) ever-smoking participants (1,463 lung cancer cases and 915 lung cancer deaths). Six-year lung cancer incidence and mortality risk predictions were assessed for (1) calibration (graphically) by comparing the agreement between the predicted and the observed risks, (2) discrimination (area under the receiver operating characteristic curve [AUC]) between individuals with and without lung cancer (death), and (3) clinical usefulness (net benefit in decision curve analysis) by identifying risk thresholds at which applying risk-based eligibility would improve lung cancer screening efficacy. To further assess performance, risk model sensitivities and specificities in the PLCO were compared to those based on the NLST eligibility criteria. Calibration was satisfactory, but discrimination ranged widely (AUCs from 0.61 to 0.81). The models outperformed the NLST eligibility criteria over a substantial range of risk thresholds in decision curve analysis, with a higher sensitivity for all models and a slightly higher specificity for some models. The PLCOm2012, Bach, and Two-Stage Clonal Expansion incidence models had the best overall performance, with AUCs >0.68 in the NLST and >0.77 in the PLCO. These three models had the highest sensitivity and specificity for predicting 6-y lung cancer incidence in the PLCO chest radiography arm, with sensitivities >79.8% and specificities >62.3%. In contrast, the NLST eligibility criteria yielded a sensitivity of 71.4% and a specificity of 62.2%. Limitations of this study include the lack of identification of optimal risk thresholds, as this requires additional information on the long-term benefits (e.g., life-years gained and mortality reduction) and harms (e.g., overdiagnosis) of risk-based screening strategies using these models. In addition, information on some predictor variables included in the risk prediction models was not available.ConclusionsSelection of individuals for lung cancer screening using individual risk is superior to selection criteria based on age and pack-years alone. T...
Renal tumor heterogeneity studies have utilized the von Hippel-Lindau VHL gene to classify disease into molecularly defined subtypes to examine associations with etiologic risk factors and prognosis. The aim of this study was to provide a comprehensive analysis of VHL inactivation in clear cell renal tumors (ccRCC) and to evaluate relationships between VHL inactivation subgroups with renal cancer risk factors and VHL germline single nucleotide polymorphisms (SNPs). VHL genetic and epigenetic inactivation was examined among 507 sporadic RCC/470 ccRCC cases using endonuclease scanning and using bisulfite treatment and Sanger sequencing across 11 CpG sites within the VHL promoter. Case-only multivariate analyses were conducted to identify associations between alteration subtypes and risk factors. VHL inactivation, either through sequence alterations or promoter methylation in tumor DNA, was observed among 86.6% of ccRCC cases. Germline VHL SNPs and a haplotype were associated with promoter hypermethylation in tumor tissue (OR = 6.10; 95% CI: 2.28–16.35, p = 3.76E-4, p-global = 8E-5). Risk of having genetic VHL inactivation was inversely associated with smoking due to a higher proportion of wild-type ccRCC tumors [former: OR = 0.70 (0.20–1.31) and current: OR = 0.56 (0.32–0.99); P-trend = 0.04]. Alteration prevalence did not differ by histopathologic characteristics or occupational exposure to trichloroethylene. ccRCC cases with particular VHL germline polymorphisms were more likely to have VHL inactivation through promoter hypermethylation than through sequence alterations in tumor DNA, suggesting that the presence of these SNPs may represent an example of facilitated epigenetic variation (an inherited propensity towards epigenetic variation) in renal tissue. A proportion of tumors from current smokers lacked VHL alterations and may represent a biologically distinct clinical entity from inactivated cases.
Background-Autism Spectrum Disorders (ASD) are neurodevelopmental disorders of complex etiology, with a recognized substantial contribution of heterogeneous genetic factors; one of the core features of ASD is a lack of affiliative behaviors.
Identification of genetic factors that interact with the apolipoprotein e4 (APOE4) allele to reduce risk for Alzheimer disease (AD) would accelerate the search for new AD drug targets. Klotho-VS heterozygosity (KL-VS HET+ status) protects against aging-associated phenotypes and cognitive decline, but whether it protects individuals who carry APOE4 from AD remains unclear.OBJECTIVES To determine if KL-VS HET+ status is associated with reduced AD risk and β-amyloid (Aβ) pathology in individuals who carry APOE4. DESIGN, SETTING, AND PARTICIPANTSThis study combined 25 independent case-control, family-based, and longitudinal AD cohorts that recruited referred and volunteer participants and made data available through public repositories. Analyses were stratified by APOE4 status. Three cohorts were used to evaluate conversion risk, 1 provided longitudinal measures of Aβ CSF and PET, and 3 provided cross-sectional measures of Aβ CSF. Genetic data were available from high-density single-nucleotide variant microarrays.
Bladder cancer results from the combined effects of environmental and genetic factors, smoking being the strongest risk factor. Evaluating absolute risks resulting from the joint effects of smoking and genetic factors is critical to evaluate the public health relevance of genetic information. Analyses included up to 3,942 cases and 5,680 controls of European background in seven studies. We tested for multiplicative and additive interactions between smoking and 12 susceptibility loci, individually and combined as a polygenic risk score (PRS). Thirty-year absolute risks and risk differences by levels of the PRS were estimated for US-males aged 50-years. Six out of 12 variants showed significant additive gene-environment interactions, most notably NAT2 (P=7×10-4) and UGT1A6 (P=8×10-4). The 30-year absolute risk of bladder cancer in US males was 6.2% for all current smokers. This risk ranged from 2.9% for current smokers in the lowest quartile of the PRS to 9.9% for current smokers in the upper quartile. Risk difference estimates indicated that 8,200 cases would be prevented if elimination of smoking occurred in 100,000 men in the upper PRS quartile, compared to 2,000 cases prevented by a similar effort in the lowest PRS quartile (P-additive =1×10-4). The impact of eliminating smoking the on number of bladder cancer cases prevented is larger for individuals at higher than lower genetic risk. Our findings could have implications for targeted prevention strategies. However, other smoking-related diseases, as well as practical and ethical considerations, need to be considered before any recommendations could be made.
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