PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-25 (57)
 

Clipboard (0)
None

Select a Filter Below

Year of Publication
1.  Results of the Two Incidence Screenings in the National Lung Screening Trial 
The New England journal of medicine  2013;369(10):920-931.
Background
The National Lung Screening Trial was conducted to determine whether three annual screenings (rounds T0, T1, and T2) with low-dose helical computed tomography (CT), as compared with chest radiography, could reduce mortality from lung cancer. We present detailed findings from the first two incidence screenings (rounds T1 and T2).
Methods
We evaluated the rate of adherence of the participants to the screening protocol, the results of screening and downstream diagnostic tests, features of the lung-cancer cases, and first-line treatments, and we estimated the performance characteristics of both screening methods.
Results
At the T1 and T2 rounds, positive screening results were observed in 27.9% and 16.8% of participants in the low-dose CT group and in 6.2% and 5.0% of participants in the radiography group, respectively. In the low-dose CT group, the sensitivity was 94.4%, the specificity was 72.6%, the positive predictive value was 2.4%, and the negative predictive value was 99.9% at T1; at T2, the positive predictive value increased to 5.2%. In the radiography group, the sensitivity was 59.6%, the specificity was 94.1%, the positive predictive value was 4.4%, and the negative predictive value was 99.8% at T1; both the sensitivity and the positive predictive value increased at T2. Among lung cancers of known stage, 87 (47.5%) were stage IA and 57 (31.1%) were stage III or IV in the low-dose CT group at T1; in the radiography group, 31 (23.5%) were stage IA and 78 (59.1%) were stage III or IV at T1. These differences in stage distribution between groups persisted at T2.
Conclusions
Low-dose CT was more sensitive in detecting early-stage lung cancers, but its measured positive predictive value was lower than that of radiography. As compared with radiography, the two annual incidence screenings with low-dose CT resulted in a decrease in the number of advanced-stage cancers diagnosed and an increase in the number of early-stage lung cancers diagnosed. (Funded by the National Cancer Institute; NLST ClinicalTrials.gov number, NCT00047385.)
doi:10.1056/NEJMoa1208962
PMCID: PMC4307922  PMID: 24004119
2.  Evaluation of the Lung Cancer Risks at Which to Screen Ever- and Never-Smokers: Screening Rules Applied to the PLCO and NLST Cohorts 
PLoS Medicine  2014;11(12):e1001764.
Martin Tammemägi and colleagues evaluate which risk groups of individuals, including nonsmokers and high-risk individuals from 65 to 80 years of age, should be screened for lung cancer using computed tomography.
Please see later in the article for the Editors' Summary
Background
Lung cancer risks at which individuals should be screened with computed tomography (CT) for lung cancer are undecided. This study's objectives are to identify a risk threshold for selecting individuals for screening, to compare its efficiency with the U.S. Preventive Services Task Force (USPSTF) criteria for identifying screenees, and to determine whether never-smokers should be screened. Lung cancer risks are compared between smokers aged 55–64 and ≥65–80 y.
Methods and Findings
Applying the PLCOm2012 model, a model based on 6-y lung cancer incidence, we identified the risk threshold above which National Lung Screening Trial (NLST, n = 53,452) CT arm lung cancer mortality rates were consistently lower than rates in the chest X-ray (CXR) arm. We evaluated the USPSTF and PLCOm2012 risk criteria in intervention arm (CXR) smokers (n = 37,327) of the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO). The numbers of smokers selected for screening, and the sensitivities, specificities, and positive predictive values (PPVs) for identifying lung cancers were assessed. A modified model (PLCOall2014) evaluated risks in never-smokers. At PLCOm2012 risk ≥0.0151, the 65th percentile of risk, the NLST CT arm mortality rates are consistently below the CXR arm's rates. The number needed to screen to prevent one lung cancer death in the 65th to 100th percentile risk group is 255 (95% CI 143 to 1,184), and in the 30th to <65th percentile risk group is 963 (95% CI 291 to −754); the number needed to screen could not be estimated in the <30th percentile risk group because of absence of lung cancer deaths. When applied to PLCO intervention arm smokers, compared to the USPSTF criteria, the PLCOm2012 risk ≥0.0151 threshold selected 8.8% fewer individuals for screening (p<0.001) but identified 12.4% more lung cancers (sensitivity 80.1% [95% CI 76.8%–83.0%] versus 71.2% [95% CI 67.6%–74.6%], p<0.001), had fewer false-positives (specificity 66.2% [95% CI 65.7%–66.7%] versus 62.7% [95% CI 62.2%–63.1%], p<0.001), and had higher PPV (4.2% [95% CI 3.9%–4.6%] versus 3.4% [95% CI 3.1%–3.7%], p<0.001). In total, 26% of individuals selected for screening based on USPSTF criteria had risks below the threshold PLCOm2012 risk ≥0.0151. Of PLCO former smokers with quit time >15 y, 8.5% had PLCOm2012 risk ≥0.0151. None of 65,711 PLCO never-smokers had PLCOm2012 risk ≥0.0151. Risks and lung cancers were significantly greater in PLCO smokers aged ≥65–80 y than in those aged 55–64 y. This study omitted cost-effectiveness analysis.
Conclusions
The USPSTF criteria for CT screening include some low-risk individuals and exclude some high-risk individuals. Use of the PLCOm2012 risk ≥0.0151 criterion can improve screening efficiency. Currently, never-smokers should not be screened. Smokers aged ≥65–80 y are a high-risk group who may benefit from screening.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Lung cancer is the most commonly occurring cancer in the world and the most common cause of cancer-related deaths. Like all cancers, lung cancer occurs when cells acquire genetic changes that allow them to grow uncontrollably and to move around the body (metastasize). The most common trigger for these genetic changes in lung cancer is exposure to cigarette smoke. Symptoms of lung cancer include a persistent cough and breathlessness. If lung cancer is diagnosed when it is confined to the lung (stage I), the tumor can often be removed surgically. Stage II tumors, which have spread into nearby lymph nodes, are usually treated with surgery plus chemotherapy or radiotherapy. For more advanced lung cancers that have spread throughout the chest (stage III) or the body (stage IV), surgery is rarely helpful and these tumors are treated with chemotherapy and radiotherapy alone. Overall, because most lung cancers are not detected until they are advanced, less than 17% of people diagnosed with lung cancer survive for five years.
Why Was This Study Done?
Screening for lung cancer—looking for early disease in healthy people—could save lives. In the US National Lung Screening Trial (NLST), annual screening with computed tomography (CT) reduced lung cancer mortality by 20% among smokers at high risk of developing cancer compared with screening with a chest X-ray. But what criteria should be used to decide who is screened for lung cancer? The US Preventive Services Task Force (USPSTF), for example, recommends annual CT screening of people who are 55–80 years old, have smoked 30 or more pack-years (one pack-year is defined as a pack of cigarettes per day for one year), and—if they are former smokers—quit smoking less than 15 years ago. However, some experts think lung cancer risk prediction models—statistical models that estimate risk based on numerous personal characteristics—should be used to select people for screening. Here, the researchers evaluate PLCOm2012, a lung cancer risk prediction model based on the incidence of lung cancer among smokers enrolled in the US Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO). Specifically, the researchers use NLST and PLCO screening trial data to identify a PLCOm2012 risk threshold for selecting people for screening and to compare the efficiency of the PLCOm2012 model and the USPSTF criteria for identifying “screenees.”
What Did the Researchers Do and Find?
By analyzing NLST data, the researchers calculated that at PLCOm2012 risk ≥0.0151, mortality (death) rates among NLST participants screened with CT were consistently below mortality rates among NLST participants screened with chest X-ray and that 255 people with a PLCOm2012 risk ≥0.0151 would need to be screened to prevent one lung cancer death. Next, they used data collected from smokers in the screened arm of the PLCO trial to compare the efficiency of the PLCOm2012 and USPSTF criteria for identifying screenees. They found that 8.8% fewer people had a PLCOm2012 risk ≥0.0151 than met USPSTF criteria for screening, but 12.4% more lung cancers were identified. Thus, using PLCOm2012 improved the sensitivity and specificity of the selection of individuals for lung cancer screening over using UPSTF criteria. Notably, 8.5% of PLCO former smokers with quit times of more than 15 years had PLCOm2012 risk ≥0.0151, none of the PLCO never-smokers had PLCOm2012 risk ≥0.0151, and the calculated risks and incidence of lung cancer were greater among PLCO smokers aged ≥65–80 years than among those aged 55–64 years.
What Do These Findings Mean?
Despite the absence of a cost-effectiveness analysis in this study, these findings suggest that the use of the PLCOm2012 risk ≥0.0151 threshold rather than USPSTF criteria for selecting individuals for lung cancer screening could improve screening efficiency. The findings have several other important implications. First, these findings suggest that screening may be justified in people who stopped smoking more than 15 years ago; USPSTF currently recommends that screening stop once an individual's quit time exceeds 15 years. Second, these findings do not support lung cancer screening among never-smokers. Finally, these findings suggest that smokers aged ≥65–80 years might benefit from screening, although the presence of additional illnesses and reduced life expectancy need to be considered before recommending the provision of routine lung cancer screening to this section of the population.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001764.
The US National Cancer Institute provides information about all aspects of lung cancer for patients and health-care professionals, including information on lung cancer screening (in English and Spanish)
Cancer Research UK also provides detailed information about lung cancer and about lung cancer screening
The UK National Health Service Choices website has a page on lung cancer that includes personal stories
MedlinePlus provides links to other sources of information about lung cancer (in English and Spanish)
Information about the USPSTF recommendations for lung cancer screening is available
doi:10.1371/journal.pmed.1001764
PMCID: PMC4251899  PMID: 25460915
3.  Longitudinal Screening Algorithm That Incorporates Change Over Time in CA125 Levels Identifies Ovarian Cancer Earlier Than a Single-Threshold Rule 
Journal of Clinical Oncology  2012;31(3):387-392.
Purpose
Longitudinal algorithms incorporate change over time in biomarker levels to individualize screening decision rules. Compared with a single-threshold (ST) rule, smaller deviations from baseline biomarker levels are required to signal disease. We demonstrated improvement in ovarian cancer early detection by using a longitudinal algorithm to monitor annual CA125 levels.
Patients and Methods
We retrospectively evaluated serial preclinical serum CA125 values measured annually in 44 incident ovarian cancer cases identified from participants in the PLCO (Prostate Lung Colorectal and Ovarian) Cancer Screening Trial to determine how frequently and to what extent the parametric empirical Bayes (PEB) longitudinal screening algorithm identifies ovarian cancer earlier than an ST rule.
Results
The PEB algorithm detected ovarian cancer earlier than an ST rule in a substantial proportion of cases. At 99% specificity, which corresponded to the ST-rule CA125 cutoff ≥ 35 U/mL that was used in the PLCO trial, 20% of cases were identified earlier by using the PEB algorithm. Among these cases, the PEB signaled abnormal CA125 values, on average, 10 months earlier and at a CA125 concentration 42% lower (20 U/mL) than the ST-rule cutoff. The proportion of cases detected earlier by the PEB algorithm and the earliness of detection increased as the specificity of the screening rule was reduced.
Conclusion
The PEB longitudinal algorithm identifies ovarian cancer earlier and at lower biomarker concentrations than an ST screening algorithm adjusted to the same specificity. Longitudinal biomarker assessment by using the PEB algorithm may have application for screening other solid tumors in which biomarkers are available.
doi:10.1200/JCO.2012.43.6691
PMCID: PMC3732015  PMID: 23248253
4.  The Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial and Its Associated Research Resource 
The Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial is a large-scale research effort conducted by the National Cancer Institute. PLCO offers an example of coordinated research by both the extramural and intramural communities of the National Institutes of Health. The purpose of this article is to describe the PLCO research resource and how it is managed and to assess the productivity and the costs associated with this resource. Such an in-depth analysis of a single large-scale project can shed light on questions such as how large-scale projects should be managed, what metrics should be used to assess productivity, and how costs can be compared with productivity metrics. A comprehensive publication analysis identified 335 primary research publications resulting from research using PLCO data and biospecimens from 2000 to 2012. By the end of 2012, a total of 9679 citations (excluding self-citations) have resulted from this body of research publications, with an average of 29.7 citations per article, and an h index of 45, which is comparable with other large-scale studies, such as the Nurses’ Health Study. In terms of impact on public health, PLCO trial results have been used by the US Preventive Services Task Force in making recommendations concerning prostate and ovarian cancer screening. The overall cost of PLCO was $454 million over 20 years, adjusted to 2011 dollars, with approximately $37 million for the collection, processing, and storage of biospecimens, including blood samples, buccal cells, and pathology tissues.
doi:10.1093/jnci/djt281
PMCID: PMC3888207  PMID: 24115361
5.  Factors associated with inadequate colorectal cancer screening with flexible sigmoidoscopy 
Cancer Epidemiology  2011;36(4):395-399.
Background and study aim
Inadequate colorectal cancer screening wastes limited endoscopic resources. We examined patients factors associated with inadequate flexible sigmoidoscopy (FSG) screening at baseline screening and repeat screening 3–5 years later in 10 geographically-dispersed screening centers participating in the ongoing Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial
Methods
A total of 64,554 participants (aged 55 – 74) completed baseline questionnaires and underwent FSG at baseline. Of these, 39,385 participants returned for repeat screening. We used logistic regression models to assess factors that are associated with inadequate FSG (defined as a study in which the depth of insertion of FSG was <50 cm or visual inspection was limited to <90% of the mucosal surface but without detection of a polyp or mass).
Results
Of 7,084 (11%) participants with inadequate FSG at baseline, 6,496 (91.7%) had <50 cm depth of insertion (75.3% due to patient discomfort) and 500 (7.1%) participants had adequate depth of insertion but suboptimal bowel preparation. Compared to 55–59 year age group, advancing age in 5-year increments (odds ratios (OR) from 1.08 to 1.51) and female sex (OR = 2.40; 95% confidence interval (CI): 2.27 – 2.54) were associated with inadequate FSG. Obesity (BMI >30 kg/m2) was associated with reduced odds (OR = 0.67; 95%CI: 0.62 – 0.72). Inadequate FSG screening at baseline was associated with inadequate FSG at repeat screening (OR = 6.24; 95%CI: 5.78 – 6.75).
Conclusions
Sedation should be considered for patients with inadequate FSG or an alternative colorectal cancer screening method should be recommended.
doi:10.1016/j.canep.2011.10.013
PMCID: PMC3288883  PMID: 22112544
Flexible sigmoidoscopy; colorectal cancer; inadequate screening; colon polyp
6.  Fine Mapping of 14q24.1 Breast Cancer Susceptibility Locus 
Human genetics  2011;131(3):479-490.
In the National Cancer Institute Cancer Genetic Markers of Susceptibility (CGEMS) genome-wide association study of breast cancer, a single nucleotide polymorphism (SNP) marker, rs999737, in the 14q24.1 interval, was associated with breast cancer risk. In order to fine map this region, we imputed a 3.93MB region flanking rs999737 for Stages 1 and 2 of the CGEMS study (5,692 cases, 5,576 controls) using the combined reference panels of the HapMap 3 and the 1000 Genomes Project. Single-marker association testing and variable-sized sliding-window haplotype analysis were performed, and for both analyses the initial tagging SNP rs999737 retained the strongest association with breast cancer risk. Investigation of contiguous regions did not reveal evidence for an additional independent signal. Therefore, we conclude that rs999737 is an optimal tag SNP for common variants in the 14q24.1 region and thus narrow the candidate variants that should be investigated in follow-up laboratory evaluation.
doi:10.1007/s00439-011-1088-4
PMCID: PMC4159746  PMID: 21959381
RAD51L1; breast cancer; genome-wide association study; fine-mapping; imputation
7.  Benefits and harms of CT lung cancer screening strategies. A comparative modeling study for the U.S. Preventive Services Task Force 
Annals of internal medicine  2014;160(5):311-320.
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.
doi:10.7326/M13-2316
PMCID: PMC4116741  PMID: 24379002
8.  Concerns and challenges in flexible sigmoidoscopy screening 
Colorectal cancer  2012;1(4):309-319.
SUMMARY
In 1992, two well-conducted case–control studies used data from two different health maintenance organizations and demonstrated a 59–79% reduction in mortality from colorectal cancer (CRC) following exposure to sigmoidoscopy. These studies highlight the possibility of reducing mortality from CRC using population-based endoscopic screening. The development of fiber optics improved the technology, and the ease of performing flexible sigmoidoscopy (FS) with widespread adoption of this screening modality. To date, FS is the only endoscopic screening modality that has been shown to reduce mortality in randomized clinical trials. This article reviews the development of sigmoidoscopy, its use in CRC screening and the current reduced role of this proven screening modality, and explores new frontiers for population-based FS screening.
doi:10.2217/crc.12.33
PMCID: PMC4108216  PMID: 25067924
9.  Cancer Screening: The Journey from Epidemiology to Policy 
Annals of epidemiology  2012;22(6):439-445.
Cancer screening procedures have brought great benefit to the public’s health. However, the science of cancer screening and the evidence arising from research in this field as it is applied to policy is complex and has been difficult to communicate, especially on the national stage. We explore how epidemiologists have contributed to this evidence base and to its translation into policy. Our essay focuses on breast and lung cancer screening to identify commonalities of experience by epidemiologists across two different cancer sites and describe how epidemiologists interact with evolving scientific and policy environments. We describe the roles and challenges that epidemiologists encounter according to the maturity of the data, stakeholders, and the related political context. We also explore the unique position of cancer screening as influenced by the legislative landscape where, due to recent healthcare reform, cancer screening research plays directly into national policy. In the complex landscape for cancer screening policy, epidemiologists can increase their impact by learning from past experiences, being well prepared and communicating effectively.
doi:10.1016/j.annepidem.2012.03.004
PMCID: PMC4096857  PMID: 22626002
Epidemiology; Public Policy; Health Policy; Cancer Screening
10.  Serum Levels of Vitamin D Metabolites and Breast Cancer Risk in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial 
Experimental and epidemiologic studies suggest that vitamin D metabolites (1,25-dihydroxyvitamin D [1,25(OH)2D] and its precursor 25-hydroxyvitamin D [25(OH)D]) may reduce breast cancer risk. We examined subsequent breast cancer risk related to serum levels of these metabolites. In a cohort of women ages 55 to 74 years, who donated blood at baseline (1993–2001) in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial, we identified 1,005 incident breast cancer cases during follow-up through 2005 (mean time between blood draw and diagnosis, 3.9 years). Noncases (n = 1,005) were frequency matched to the cases based on age and year of entry. Sample weights that accounted for unequal probabilities of selecting cases and noncases were applied to make inferences that reflected the entire Prostate, Lung, Colorectal, and Ovarian cohort. Using Cox proportional hazards modeling, we computed breast cancer relative risks (RR) and 95% confidence intervals (95% CI) by quintile for each metabolite. The RR of breast cancer for the highest quintile of 25(OH)D concentration versus the lowest was 1.04 (95% CI, 0.75–1.45; Ptrend = 0.81). Similarly, the breast cancer RR for the highest quintile of 1,25(OH)2D compared with the lowest was 1.23 (95% CI, 0.91–1.68; Ptrend = 0.14). Excluding the first 2 years of follow-up did not materially alter these estimates. There was also no evidence of inverse risk in older women (≥60 years) versus younger women (<60 years). In this prospective study of postmenopausal women, we did not observe an inverse association between circulating 25(OH)D or 1,25(OH)2D and breast cancer risk, although we cannot exclude an association in younger women or with long-term or earlier exposure.
doi:10.1158/1055-9965.EPI-07-2594
PMCID: PMC4039037  PMID: 18381472
11.  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 pre-diagnostic samples to assess the potential of the panels for early detection. We conducted a multi-site systematic evaluation of biomarker panels using pre-diagnostic 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 6–8 biomarkers, were evaluated according to a pre-determined 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 pre-diagnostic samples; utilizing pre-diagnostic samples for discovery may be helpful in developing validated early detection panels.
doi:10.1158/1940-6207.CAPR-10-0193
PMCID: PMC3057372  PMID: 21372037
Early Detection; Screening; Biomarkers; Validation; Study Design
12.  Genome-wide association studies identify four ER negative–specific breast cancer risk loci 
Garcia-Closas, Montserrat | Couch, Fergus J | Lindstrom, Sara | Michailidou, Kyriaki | Schmidt, Marjanka K | Brook, Mark N | orr, Nick | Rhie, Suhn Kyong | Riboli, Elio | Feigelson, Heather s | Le Marchand, Loic | Buring, Julie E | Eccles, Diana | Miron, Penelope | Fasching, Peter A | Brauch, Hiltrud | Chang-Claude, Jenny | Carpenter, Jane | Godwin, Andrew K | Nevanlinna, Heli | Giles, Graham G | Cox, Angela | Hopper, John L | Bolla, Manjeet K | Wang, Qin | Dennis, Joe | Dicks, Ed | Howat, Will J | Schoof, Nils | Bojesen, Stig E | Lambrechts, Diether | Broeks, Annegien | Andrulis, Irene L | Guénel, Pascal | Burwinkel, Barbara | Sawyer, Elinor J | Hollestelle, Antoinette | Fletcher, Olivia | Winqvist, Robert | Brenner, Hermann | Mannermaa, Arto | Hamann, Ute | Meindl, Alfons | Lindblom, Annika | Zheng, Wei | Devillee, Peter | Goldberg, Mark S | Lubinski, Jan | Kristensen, Vessela | Swerdlow, Anthony | Anton-Culver, Hoda | Dörk, Thilo | Muir, Kenneth | Matsuo, Keitaro | Wu, Anna H | Radice, Paolo | Teo, Soo Hwang | Shu, Xiao-Ou | Blot, William | Kang, Daehee | Hartman, Mikael | Sangrajrang, Suleeporn | Shen, Chen-Yang | Southey, Melissa C | Park, Daniel J | Hammet, Fleur | Stone, Jennifer | Veer, Laura J Van’t | Rutgers, Emiel J | Lophatananon, Artitaya | Stewart-Brown, Sarah | Siriwanarangsan, Pornthep | Peto, Julian | Schrauder, Michael G | Ekici, Arif B | Beckmann, Matthias W | Silva, Isabel dos Santos | Johnson, Nichola | Warren, Helen | Tomlinson, Ian | Kerin, Michael J | Miller, Nicola | Marme, Federick | Schneeweiss, Andreas | Sohn, Christof | Truong, Therese | Laurent-Puig, Pierre | Kerbrat, Pierre | Nordestgaard, Børge G | Nielsen, Sune F | Flyger, Henrik | Milne, Roger L | Perez, Jose Ignacio Arias | Menéndez, Primitiva | Müller, Heiko | Arndt, Volker | Stegmaier, Christa | Lichtner, Peter | Lochmann, Magdalena | Justenhoven, Christina | Ko, Yon-Dschun | Muranen, Taru A | Aittomäki, Kristiina | Blomqvist, Carl | Greco, Dario | Heikkinen, Tuomas | Ito, Hidemi | Iwata, Hiroji | Yatabe, Yasushi | Antonenkova, Natalia N | Margolin, Sara | Kataja, Vesa | Kosma, Veli-Matti | Hartikainen, Jaana M | Balleine, Rosemary | Tseng, Chiu-Chen | Van Den Berg, David | Stram, Daniel O | Neven, Patrick | Dieudonné, Anne-Sophie | Leunen, Karin | Rudolph, Anja | Nickels, Stefan | Flesch-Janys, Dieter | Peterlongo, Paolo | Peissel, Bernard | Bernard, Loris | Olson, Janet E | Wang, Xianshu | Stevens, Kristen | Severi, Gianluca | Baglietto, Laura | Mclean, Catriona | Coetzee, Gerhard A | Feng, Ye | Henderson, Brian E | Schumacher, Fredrick | Bogdanova, Natalia V | Labrèche, France | Dumont, Martine | Yip, Cheng Har | Taib, Nur Aishah Mohd | Cheng, Ching-Yu | Shrubsole, Martha | Long, Jirong | Pylkäs, Katri | Jukkola-Vuorinen, Arja | Kauppila, Saila | knight, Julia A | Glendon, Gord | Mulligan, Anna Marie | Tollenaar, Robertus A E M | Seynaeve, Caroline M | Kriege, Mieke | Hooning, Maartje J | Van den Ouweland, Ans M W | Van Deurzen, Carolien H M | Lu, Wei | Gao, Yu-Tang | Cai, Hui | Balasubramanian, Sabapathy P | Cross, Simon S | Reed, Malcolm W R | Signorello, Lisa | Cai, Qiuyin | Shah, Mitul | Miao, Hui | Chan, Ching Wan | Chia, Kee Seng | Jakubowska, Anna | Jaworska, Katarzyna | Durda, Katarzyna | Hsiung, Chia-Ni | Wu, Pei-Ei | Yu, Jyh-Cherng | Ashworth, Alan | Jones, Michael | Tessier, Daniel C | González-Neira, Anna | Pita, Guillermo | Alonso, M Rosario | Vincent, Daniel | Bacot, Francois | Ambrosone, Christine B | Bandera, Elisa V | John, Esther M | Chen, Gary K | Hu, Jennifer J | Rodriguez-gil, Jorge L | Bernstein, Leslie | Press, Michael F | Ziegler, Regina G | Millikan, Robert M | Deming-Halverson, Sandra L | Nyante, Sarah | Ingles, Sue A | Waisfisz, Quinten | Tsimiklis, Helen | Makalic, Enes | Schmidt, Daniel | Bui, Minh | Gibson, Lorna | Müller-Myhsok, Bertram | Schmutzler, Rita K | Hein, Rebecca | Dahmen, Norbert | Beckmann, Lars | Aaltonen, Kirsimari | Czene, Kamila | Irwanto, Astrid | Liu, Jianjun | Turnbull, Clare | Rahman, Nazneen | Meijers-Heijboer, Hanne | Uitterlinden, Andre G | Rivadeneira, Fernando | Olswold, Curtis | Slager, Susan | Pilarski, Robert | Ademuyiwa, Foluso | Konstantopoulou, Irene | Martin, Nicholas G | Montgomery, Grant W | Slamon, Dennis J | Rauh, Claudia | Lux, Michael P | Jud, Sebastian M | Bruning, Thomas | Weaver, Joellen | Sharma, Priyanka | Pathak, Harsh | Tapper, Will | Gerty, Sue | Durcan, Lorraine | Trichopoulos, Dimitrios | Tumino, Rosario | Peeters, Petra H | Kaaks, Rudolf | Campa, Daniele | Canzian, Federico | Weiderpass, Elisabete | Johansson, Mattias | Khaw, Kay-Tee | Travis, Ruth | Clavel-Chapelon, Françoise | Kolonel, Laurence N | Chen, Constance | Beck, Andy | Hankinson, Susan E | Berg, Christine D | Hoover, Robert N | Lissowska, Jolanta | Figueroa, Jonine D | Chasman, Daniel I | Gaudet, Mia M | Diver, W Ryan | Willett, Walter C | Hunter, David J | Simard, Jacques | Benitez, Javier | Dunning, Alison M | Sherman, Mark E | Chenevix-Trench, Georgia | Chanock, Stephen J | Hall, Per | Pharoah, Paul D P | Vachon, Celine | Easton, Douglas F | Haiman, Christopher A | Kraft, Peter
Nature genetics  2013;45(4):392-398e2.
Estrogen receptor (ER)-negative tumors represent 20–30% of all breast cancers, with a higher proportion occurring in younger women and women of African ancestry1. The etiology2 and clinical behavior3 of ER-negative tumors are different from those of tumors expressing ER (ER positive), including differences in genetic predisposition4. To identify susceptibility loci specific to ER-negative disease, we combined in a meta-analysis 3 genome-wide association studies of 4,193 ER-negative breast cancer cases and 35,194 controls with a series of 40 follow-up studies (6,514 cases and 41,455 controls), genotyped using a custom Illumina array, iCOGS, developed by the Collaborative Oncological Gene-environment Study (COGS). SNPs at four loci, 1q32.1 (MDM4, P = 2.1 × 10−12 and LGR6, P = 1.4 × 10−8), 2p24.1 (P = 4.6 × 10−8) and 16q12.2 (FTO, P = 4.0 × 10−8), were associated with ER-negative but not ER-positive breast cancer (P > 0.05). These findings provide further evidence for distinct etiological pathways associated with invasive ER-positive and ER-negative breast cancers.
doi:10.1038/ng.2561
PMCID: PMC3771695  PMID: 23535733
13.  Probability of Cancer in Pulmonary Nodules Detected on First Screening CT 
The New England journal of medicine  2013;369(10):910-919.
BACKGROUND
Major issues in the implementation of screening for lung cancer by means of low-dose computed tomography (CT) are the definition of a positive result and the management of lung nodules detected on the scans. We conducted a population-based prospective study to determine factors predicting the probability that lung nodules detected on the first screening low-dose CT scans are malignant or will be found to be malignant on follow-up.
METHODS
We analyzed data from two cohorts of participants undergoing low-dose CT screening. The development data set included participants in the Pan-Canadian Early Detection of Lung Cancer Study (PanCan). The validation data set included participants involved in chemoprevention trials at the British Columbia Cancer Agency (BCCA), sponsored by the U.S. National Cancer Institute. The final outcomes of all nodules of any size that were detected on baseline low-dose CT scans were tracked. Parsimonious and fuller multivariable logistic-regression models were prepared to estimate the probability of lung cancer.
RESULTS
In the PanCan data set, 1871 persons had 7008 nodules, of which 102 were malignant, and in the BCCA data set, 1090 persons had 5021 nodules, of which 42 were malignant. Among persons with nodules, the rates of cancer in the two data sets were 5.5% and 3.7%, respectively. Predictors of cancer in the model included older age, female sex, family history of lung cancer, emphysema, larger nodule size, location of the nodule in the upper lobe, part-solid nodule type, lower nodule count, and spiculation. Our final parsimonious and full models showed excellent discrimination and calibration, with areas under the receiver-operating-characteristic curve of more than 0.90, even for nodules that were 10 mm or smaller in the validation set.
CONCLUSIONS
Predictive tools based on patient and nodule characteristics can be used to accurately estimate the probability that lung nodules detected on baseline screening low-dose CT scans are malignant. (Funded by the Terry Fox Research Institute and others; ClinicalTrials.gov number, NCT00751660.)
doi:10.1056/NEJMoa1214726
PMCID: PMC3951177  PMID: 24004118
14.  Selection Criteria for Lung-Cancer Screening 
The New England journal of medicine  2013;368(8):728-736.
BACKGROUND
The National Lung Screening Trial (NLST) used risk factors for lung cancer (e.g., ≥30 pack-years of smoking and <15 years since quitting) as selection criteria for lung-cancer screening. Use of an accurate model that incorporates additional risk factors to select persons for screening may identify more persons who have lung cancer or in whom lung cancer will develop.
METHODS
We modified the 2011 lung-cancer risk-prediction model from our Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial to ensure applicability to NLST data; risk was the probability of a diagnosis of lung cancer during the 6-year study period. We developed and validated the model (PLCOM2012) with data from the 80,375 persons in the PLCO control and intervention groups who had ever smoked. Discrimination (area under the receiver-operating-characteristic curve [AUC]) and calibration were assessed. In the validation data set, 14,144 of 37,332 persons (37.9%) met NLST criteria. For comparison, 14,144 highest-risk persons were considered positive (eligible for screening) according to PLCOM2012 criteria. We compared the accuracy of PLCOM2012 criteria with NLST criteria to detect lung cancer. Cox models were used to evaluate whether the reduction in mortality among 53,202 persons undergoing low-dose computed tomographic screening in the NLST differed according to risk.
RESULTS
The AUC was 0.803 in the development data set and 0.797 in the validation data set. As compared with NLST criteria, PLCOM2012 criteria had improved sensitivity (83.0% vs. 71.1%, P<0.001) and positive predictive value (4.0% vs. 3.4%, P = 0.01), without loss of specificity (62.9% and. 62.7%, respectively; P = 0.54); 41.3% fewer lung cancers were missed. The NLST screening effect did not vary according to PLCOM2012 risk (P = 0.61 for interaction).
CONCLUSIONS
The use of the PLCOM2012 model was more sensitive than the NLST criteria for lung-cancer detection.
doi:10.1056/NEJMoa1211776
PMCID: PMC3929969  PMID: 23425165
15.  A Genome-Wide “Pleiotropy Scan” Does Not Identify New Susceptibility Loci for Estrogen Receptor Negative Breast Cancer 
PLoS ONE  2014;9(2):e85955.
Approximately 15–30% of all breast cancer tumors are estrogen receptor negative (ER−). Compared with ER-positive (ER+) disease they have an earlier age at onset and worse prognosis. Despite the vast number of risk variants identified for numerous cancer types, only seven loci have been unambiguously identified for ER-negative breast cancer. With the aim of identifying new susceptibility SNPs for this disease we performed a pleiotropic genome-wide association study (GWAS). We selected 3079 SNPs associated with a human complex trait or disease at genome-wide significance level (P<5×10−8) to perform a secondary analysis of an ER-negative GWAS from the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium (BPC3), including 1998 cases and 2305 controls from prospective studies. We then tested the top ten associations (i.e. with the lowest P-values) using three additional populations with a total sample size of 3509 ER+ cases, 2543 ER− cases and 7031 healthy controls. None of the 3079 selected variants in the BPC3 ER-GWAS were significant at the adjusted threshold. 186 variants were associated with ER− breast cancer risk at a conventional threshold of P<0.05, with P-values ranging from 0.049 to 2.3×10−4. None of the variants reached statistical significance in the replication phase. In conclusion, this study did not identify any novel susceptibility loci for ER-breast cancer using a “pleiotropic approach”.
doi:10.1371/journal.pone.0085955
PMCID: PMC3921107  PMID: 24523857
16.  Targeting of Low-Dose CT Screening According to the Risk of Lung-Cancer Death 
The New England journal of medicine  2013;369(3):245-254.
BACKGROUND
In the National Lung Screening Trial (NLST), screening with low-dose computed tomography (CT) resulted in a 20% reduction in lung-cancer mortality among participants between the ages of 55 and 74 years with a minimum of 30 pack-years of smoking and no more than 15 years since quitting. It is not known whether the benefits and potential harms of such screening vary according to lung-cancer risk.
METHODS
We assessed the variation in efficacy, the number of false positive results, and the number of lung-cancer deaths prevented among 26,604 participants in the NLST who underwent low-dose CT screening, as compared with the 26,554 participants who underwent chest radiography, according to the quintile of 5-year risk of lung-cancer death (ranging from 0.15 to 0.55% in the lowest-risk group [quintile 1] to more than 2.00% in the highest-risk group [quintile 5]).
RESULTS
The number of lung-cancer deaths per 10,000 person-years that were prevented in the CT-screening group, as compared with the radiography group, increased according to risk quintile (0.2 in quintile 1, 3.5 in quintile 2, 5.1 in quintile 3, 11.0 in quintile 4, and 12.0 in quintile 5; P = 0.01 for trend). Across risk quintiles, there were significant decreasing trends in the number of participants with false positive results per screening-prevented lung-cancer death (1648 in quintile 1, 181 in quintile 2, 147 in quintile 3, 64 in quintile 4, and 65 in quintile 5). The 60% of participants at highest risk for lung-cancer death (quintiles 3 through 5) accounted for 88% of the screening-prevented lung-cancer deaths and for 64% of participants with false positive results. The 20% of participants at lowest risk (quintile 1) accounted for only 1% of prevented lung-cancer deaths.
CONCLUSIONS
Screening with low-dose CT prevented the greatest number of deaths from lung cancer among participants who were at highest risk and prevented very few deaths among those at lowest risk. These findings provide empirical support for risk-based targeting of smokers for such screening. (Funded by the National Cancer Institute.)
doi:10.1056/NEJMoa1301851
PMCID: PMC3783654  PMID: 23863051
17.  Thyroid Cancer Rates and 131I Doses from Nevada Atmospheric Nuclear Bomb Tests: An Update 
Radiation research  2010;173(5):10.1667/RR2057.1.
Exposure to radioactive iodine (131I) from atmospheric nuclear tests conducted in Nevada in the 1950s may have increased thyroid cancer risks. To investigate the long-term effects of this exposure, we analyzed data on thyroid cancer incidence (18,545 cases) from eight Surveillance, Epidemiology, and End Results (SEER) tumor registries for the period 1973-2004. Excess relative risks (ERR) per Gray (Gy) for exposure received before age 15 were estimated by relating age-, birth year-, sex-, and county-specific thyroid cancer rates to estimates of cumulative dose to the thyroid that take age into account. The estimated ERR per Gy for dose received before one year of age was 1.8 (95% confidence interval (CI), 0.5-3.2). There was no evidence that this estimate declined with follow-up time or that risk increased with dose received at ages 1-15. These results confirm earlier findings based on less extensive data for the period 1973-1994. The lack of a dose-response for those exposed at ages 1-15 is inconsistent with studies of children exposed to external radiation or 131I from the Chernobyl accident, and results need to be interpreted in light of limitations and biases inherent in ecologic studies, including the error in doses and case ascertainment resulting from migration. Nevertheless, the study adds support for an increased risk of thyroid cancer due to fallout, although the data are inadequate to quantify it.
doi:10.1667/RR2057.1
PMCID: PMC3865880  PMID: 20426666
18.  A meta-analysis of genome-wide association studies of breast cancer identifies two novel susceptibility loci at 6q14 and 20q11 
Siddiq, Afshan | Couch, Fergus J. | Chen, Gary K. | Lindström, Sara | Eccles, Diana | Millikan, Robert C. | Michailidou, Kyriaki | Stram, Daniel O. | Beckmann, Lars | Rhie, Suhn Kyong | Ambrosone, Christine B. | Aittomäki, Kristiina | Amiano, Pilar | Apicella, Carmel | Baglietto, Laura | Bandera, Elisa V. | Beckmann, Matthias W. | Berg, Christine D. | Bernstein, Leslie | Blomqvist, Carl | Brauch, Hiltrud | Brinton, Louise | Bui, Quang M. | Buring, Julie E. | Buys, Saundra S. | Campa, Daniele | Carpenter, Jane E. | Chasman, Daniel I. | Chang-Claude, Jenny | Chen, Constance | Clavel-Chapelon, Françoise | Cox, Angela | Cross, Simon S. | Czene, Kamila | Deming, Sandra L. | Diasio, Robert B. | Diver, W. Ryan | Dunning, Alison M. | Durcan, Lorraine | Ekici, Arif B. | Fasching, Peter A. | Feigelson, Heather Spencer | Fejerman, Laura | Figueroa, Jonine D. | Fletcher, Olivia | Flesch-Janys, Dieter | Gaudet, Mia M. | Gerty, Susan M. | Rodriguez-Gil, Jorge L. | Giles, Graham G. | van Gils, Carla H. | Godwin, Andrew K. | Graham, Nikki | Greco, Dario | Hall, Per | Hankinson, Susan E. | Hartmann, Arndt | Hein, Rebecca | Heinz, Judith | Hoover, Robert N. | Hopper, John L. | Hu, Jennifer J. | Huntsman, Scott | Ingles, Sue A. | Irwanto, Astrid | Isaacs, Claudine | Jacobs, Kevin B. | John, Esther M. | Justenhoven, Christina | Kaaks, Rudolf | Kolonel, Laurence N. | Coetzee, Gerhard A. | Lathrop, Mark | Le Marchand, Loic | Lee, Adam M. | Lee, I-Min | Lesnick, Timothy | Lichtner, Peter | Liu, Jianjun | Lund, Eiliv | Makalic, Enes | Martin, Nicholas G. | McLean, Catriona A. | Meijers-Heijboer, Hanne | Meindl, Alfons | Miron, Penelope | Monroe, Kristine R. | Montgomery, Grant W. | Müller-Myhsok, Bertram | Nickels, Stefan | Nyante, Sarah J. | Olswold, Curtis | Overvad, Kim | Palli, Domenico | Park, Daniel J. | Palmer, Julie R. | Pathak, Harsh | Peto, Julian | Pharoah, Paul | Rahman, Nazneen | Rivadeneira, Fernando | Schmidt, Daniel F. | Schmutzler, Rita K. | Slager, Susan | Southey, Melissa C. | Stevens, Kristen N. | Sinn, Hans-Peter | Press, Michael F. | Ross, Eric | Riboli, Elio | Ridker, Paul M. | Schumacher, Fredrick R. | Severi, Gianluca | dos Santos Silva, Isabel | Stone, Jennifer | Sund, Malin | Tapper, William J. | Thun, Michael J. | Travis, Ruth C. | Turnbull, Clare | Uitterlinden, Andre G. | Waisfisz, Quinten | Wang, Xianshu | Wang, Zhaoming | Weaver, JoEllen | Schulz-Wendtland, Rüdiger | Wilkens, Lynne R. | Van Den Berg, David | Zheng, Wei | Ziegler, Regina G. | Ziv, Elad | Nevanlinna, Heli | Easton, Douglas F. | Hunter, David J. | Henderson, Brian E. | Chanock, Stephen J. | Garcia-Closas, Montserrat | Kraft, Peter | Haiman, Christopher A. | Vachon, Celine M.
Human Molecular Genetics  2012;21(24):5373-5384.
Genome-wide association studies (GWAS) of breast cancer defined by hormone receptor status have revealed loci contributing to susceptibility of estrogen receptor (ER)-negative subtypes. To identify additional genetic variants for ER-negative breast cancer, we conducted the largest meta-analysis of ER-negative disease to date, comprising 4754 ER-negative cases and 31 663 controls from three GWAS: NCI Breast and Prostate Cancer Cohort Consortium (BPC3) (2188 ER-negative cases; 25 519 controls of European ancestry), Triple Negative Breast Cancer Consortium (TNBCC) (1562 triple negative cases; 3399 controls of European ancestry) and African American Breast Cancer Consortium (AABC) (1004 ER-negative cases; 2745 controls). We performed in silico replication of 86 SNPs at P ≤ 1 × 10-5 in an additional 11 209 breast cancer cases (946 with ER-negative disease) and 16 057 controls of Japanese, Latino and European ancestry. We identified two novel loci for breast cancer at 20q11 and 6q14. SNP rs2284378 at 20q11 was associated with ER-negative breast cancer (combined two-stage OR = 1.16; P = 1.1 × 10−8) but showed a weaker association with overall breast cancer (OR = 1.08, P = 1.3 × 10–6) based on 17 869 cases and 43 745 controls and no association with ER-positive disease (OR = 1.01, P = 0.67) based on 9965 cases and 22 902 controls. Similarly, rs17530068 at 6q14 was associated with breast cancer (OR = 1.12; P = 1.1 × 10−9), and with both ER-positive (OR = 1.09; P = 1.5 × 10−5) and ER-negative (OR = 1.16, P = 2.5 × 10−7) disease. We also confirmed three known loci associated with ER-negative (19p13) and both ER-negative and ER-positive breast cancer (6q25 and 12p11). Our results highlight the value of large-scale collaborative studies to identify novel breast cancer risk loci.
doi:10.1093/hmg/dds381
PMCID: PMC3510753  PMID: 22976474
19.  Prediction of breast cancer risk by genetic risk factors, overall and by hormone receptor status 
Journal of medical genetics  2012;49(9):601-608.
Objective
There is increasing interest in adding common genetic variants identified through genome wide association studies (GWAS) to breast cancer risk prediction models. First results from such models showed modest benefits in terms of risk discrimination. Heterogeneity of breast cancer as defined by hormone-receptor status has not been considered in this context. In this study we investigated the predictive capacity of 32 GWAS-detected common variants for breast cancer risk, alone and in combination with classical risk factors, and for tumors with different hormone receptor status.
Material and Methods
Within the Breast and Prostate Cancer Cohort Consortium (BPC3), we analyzed 6009 invasive breast cancer cases and 7827 matched controls of European ancestry, with data on classical breast cancer risk factors and 32 common gene variants identified through GWAS. Discriminatory ability with respect to breast cancer of specific hormone receptor-status was assessed with the age- and cohort-adjusted concordance statistic (AUROCa). Absolute risk scores were calculated with external reference data. Integrated discrimination improvement (IDI) was used to measure improvements in risk prediction.
Results
We found a small but steady increase in discriminatory ability with increasing numbers of genetic variants included in the model (difference in AUROCa going from 2.7 to 4%). Discriminatory ability for all models varied strongly by hormone receptor status
Discussion and Conclusion
Adding information on common polymorphisms provides small but statistically significant improvements in the quality of breast cancer risk prediction models. We consistently observed better performance for receptor positive cases, but the gain in discriminatory quality is not sufficient for clinical application.
doi:10.1136/jmedgenet-2011-100716
PMCID: PMC3793888  PMID: 22972951
breast cancer; risk prediction; genetic factors; hormone receptor status
20.  Screening for lung cancer with low-dose computed tomography: a review of current status 
Journal of Thoracic Disease  2013;5(Suppl 5):S524-S539.
Screening using low-dose computed tomography (CT) represents an exciting new development in the struggle to improve outcomes for people with lung cancer. Randomised controlled evidence demonstrating a 20% relative lung cancer mortality benefit has led to endorsement of screening by several expert bodies in the US and funding by healthcare providers. Despite this pivotal result, many questions remain regarding technical and logistical aspects of screening, cost-effectiveness and generalizability to other settings. This review discusses the rationale behind screening, the results of on-going trials, potential harms of screening and current knowledge gaps.
doi:10.3978/j.issn.2072-1439.2013.09.06
PMCID: PMC3804881  PMID: 24163745
Lung neoplasms/mortality; mass screening tomography; helical computed; early detection of cancer/methods
21.  The chromosome 2p21 region harbors a complex genetic architecture for association with risk for renal cell carcinoma 
Human Molecular Genetics  2011;21(5):1190-1200.
In follow-up of a recent genome-wide association study (GWAS) that identified a locus in chromosome 2p21 associated with risk for renal cell carcinoma (RCC), we conducted a fine mapping analysis of a 120 kb region that includes EPAS1. We genotyped 59 tagged common single-nucleotide polymorphisms (SNPs) in 2278 RCC and 3719 controls of European background and observed a novel signal for rs9679290 [P = 5.75 × 10−8, per-allele odds ratio (OR) = 1.27, 95% confidence interval (CI): 1.17–1.39]. Imputation of common SNPs surrounding rs9679290 using HapMap 3 and 1000 Genomes data yielded two additional signals, rs4953346 (P = 4.09 × 10−14) and rs12617313 (P = 7.48 × 10−12), both highly correlated with rs9679290 (r2 > 0.95), but interestingly not correlated with the two SNPs reported in the GWAS: rs11894252 and rs7579899 (r2 < 0.1 with rs9679290). Genotype analysis of rs12617313 confirmed an association with RCC risk (P = 1.72 × 10−9, per-allele OR = 1.28, 95% CI: 1.18–1.39) In conclusion, we report that chromosome 2p21 harbors a complex genetic architecture for common RCC risk variants.
doi:10.1093/hmg/ddr551
PMCID: PMC3277315  PMID: 22113997
22.  Estrogen Metabolism and Risk of Breast Cancer in Postmenopausal Women 
Background
Estrogens are recognized causal factors in breast cancer. Interindividual variation in estrogen metabolism may also influence the risk of breast cancer and could provide clues to mechanisms of breast carcinogenesis. Long-standing hypotheses about how estrogen metabolism might influence breast cancer have not been adequately evaluated in epidemiological studies because of the lack of accurate, reproducible, and high-throughput assays for estrogen metabolites.
Methods
We conducted a prospective case–control study nested within the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO). Participants included 277 women who developed invasive breast cancer (case subjects) and 423 matched control subjects; at PLCO baseline, all subjects were aged 55–74 years, postmenopausal and not using hormone therapy, and provided a blood sample. Liquid chromatography–tandem mass spectrometry was used to measure serum concentrations of 15 estrogens and estrogen metabolites, in unconjugated and conjugated forms, including the parent estrogens, estrone and estradiol, and estrogen metabolites in pathways defined by irreversible hydroxylation at the C-2, C-4, or C-16 positions of the steroid ring. We calculated hazard ratios (HRs) approximating risk in highest vs lowest deciles of individual estrogens and estrogen metabolites, estrogens and estrogen metabolites grouped by metabolic pathways, and metabolic pathway ratios using multivariable Cox proportional hazards models. All statistical tests were two-sided.
Results
Nearly all estrogens, estrogen metabolites, and metabolic pathway groups were associated with an increased risk of breast cancer; the serum concentration of unconjugated estradiol was strongly associated with the risk of breast cancer (HR = 2.07, 95% confidence interval [CI] = 1.19 to 3.62). No estrogen, estrogen metabolite, or metabolic pathway group remained statistically significantly associated with the risk of breast cancer after adjusting for unconjugated estradiol. The ratio of the 2-hydroxylation pathway to parent estrogens (HR = 0.66, 95% CI = 0.51 to 0.87) and the ratio of 4-hydroxylation pathway catechols to 4-hydroxylation pathway methylated catechols (HR = 1.34, 95% CI = 1.04 to 1.72) were statistically significantly associated with the risk of breast cancer and remained so after adjustment for unconjugated estradiol.
Conclusions
More extensive 2-hydroxylation of parent estrogens is associated with lower risk, and less extensive methylation of potentially genotoxic 4-hydroxylation pathway catechols is associated with higher risk of postmenopausal breast cancer.
doi:10.1093/jnci/djr531
PMCID: PMC3283536  PMID: 22232133
23.  Flexible Sigmoidoscopy in the Randomized Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial: Added Yield from a Second Screening Examination 
Background
Among randomized trials evaluating flexible sigmoidoscopy (FSG) for its effect on colorectal cancer mortality, only the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial screened its participants more than one time. We report outcomes from the PLCO screening FSG program and evaluate the increased yield produced by a second FSG.
Methods
Participants were screened by 60-cm FSG in 10 regional screening centers at study entry and 3 or 5 years later, depending on the time of random assignment. Results from subsequent diagnostic intervention were tracked and recorded in a standardized fashion, and outcomes were compared according to sex and age. The protocol discouraged repeat FSG in persons with colorectal cancer or adenoma diagnosed after the initial FSG.
Results
Of 77 447 enrollees, 67 073 (86.6%) had at least one FSG and 39 443 (50.9%) had two FSGs. Diagnostic intervention occurred in 74.9% after a positive first FSG and in 78.7% after a positive repeat FSG. The second FSG increased the screening yield by 32%: Colorectal cancer or advanced adenoma was detected in 37.8 per 1000 persons after first screening and in 49.8 per 1000 persons after all screenings. The second FSG increased the yield of cancer or advanced adenoma by 26% in women and by 34% in men. Of 223 subjects who received a diagnosis of colorectal carcinoma within 1 year of a positive FSG, 64.6% had stage I and 17.5% had stage II disease.
Conclusions
Repeat FSG increased the detection of colorectal cancer or advanced adenoma in women by one-fourth and in men by one-third. Screen-detected carcinomas were early stage (stage I or II) in greater than 80% of screened persons. Colorectal cancer mortality data from the PLCO, as the definitive endpoint, will follow in later publications.
doi:10.1093/jnci/djr549
PMCID: PMC3283538  PMID: 22298838
24.  A genome-wide association study identifies a novel susceptibility locus for renal cell carcinoma on 12p11.23 
Wu, Xifeng | Scelo, Ghislaine | Purdue, Mark P. | Rothman, Nathaniel | Johansson, Mattias | Ye, Yuanqing | Wang, Zhaoming | Zelenika, Diana | Moore, Lee E. | Wood, Christopher G. | Prokhortchouk, Egor | Gaborieau, Valerie | Jacobs, Kevin B. | Chow, Wong-Ho | Toro, Jorge R. | Zaridze, David | Lin, Jie | Lubinski, Jan | Trubicka, Joanna | Szeszenia-Dabrowska, Neonilia | Lissowska, Jolanta | Rudnai, Peter | Fabianova, Eleonora | Mates, Dana | Jinga, Viorel | Bencko, Vladimir | Slamova, Alena | Holcatova, Ivana | Navratilova, Marie | Janout, Vladimir | Boffetta, Paolo | Colt, Joanne S. | Davis, Faith G. | Schwartz, Kendra L. | Banks, Rosamonde E. | Selby, Peter J. | Harnden, Patricia | Berg, Christine D. | Hsing, Ann W. | Grubb, Robert L. | Boeing, Heiner | Vineis, Paolo | Clavel-Chapelon, Françoise | Palli, Domenico | Tumino, Rosario | Krogh, Vittorio | Panico, Salvatore | Duell, Eric J. | Quirós, José Ramón | Sanchez, Maria-José | Navarro, Carmen | Ardanaz, Eva | Dorronsoro, Miren | Khaw, Kay-Tee | Allen, Naomi E. | Bueno-de-Mesquita, H. Bas | Peeters, Petra H.M. | Trichopoulos, Dimitrios | Linseisen, Jakob | Ljungberg, Börje | Overvad, Kim | Tjønneland, Anne | Romieu, Isabelle | Riboli, Elio | Stevens, Victoria L | Thun, Michael J | Diver, W. Ryan | Gapstur, Susan M. | Pharoah, Paul D. | Easton, Douglas F. | Albanes, Demetrius | Virtamo, Jarmo | Vatten, Lars | Hveem, Kristian | Fletcher, Tony | Koppova, Kvetoslava | Cussenot, Olivier | Cancel-Tassin, Geraldine | Benhamou, Simone | Hildebrandt, Michelle A. | Pu, Xia | Foglio, Mario | Lechner, Doris | Hutchinson, Amy | Yeager, Meredith | Fraumeni, Joseph F. | Lathrop, Mark | Skryabin, Konstantin G. | McKay, James D. | Gu, Jian | Brennan, Paul | Chanock, Stephen J.
Human Molecular Genetics  2011;21(2):456-462.
Renal cell carcinoma (RCC) is the most lethal urologic cancer. Only two common susceptibility loci for RCC have been confirmed to date. To identify additional RCC common susceptibility loci, we conducted an independent genome-wide association study (GWAS). We analyzed 533 191 single nucleotide polymorphisms (SNPs) for association with RCC in 894 cases and 1516 controls of European descent recruited from MD Anderson Cancer Center in the primary scan, and validated the top 500 SNPs in silico in 3772 cases and 8505 controls of European descent involved in the only published GWAS of RCC. We identified two common variants in linkage disequilibrium, rs718314 and rs1049380 (r2 = 0.64, D ′ = 0.84), in the inositol 1,4,5-triphosphate receptor, type 2 (ITPR2) gene on 12p11.23 as novel susceptibility loci for RCC (P = 8.89 × 10−10 and P = 6.07 × 10−9, respectively, in meta-analysis) with an allelic odds ratio of 1.19 [95% confidence interval (CI): 1.13–1.26] for rs718314 and 1.18 (95% CI: 1.12–1.25) for rs1049380. It has been recently identified that rs718314 in ITPR2 is associated with waist–hip ratio (WHR) phenotype. To our knowledge, this is the first genetic locus associated with both cancer risk and WHR.
doi:10.1093/hmg/ddr479
PMCID: PMC3276284  PMID: 22010048
25.  A common variant at the TERT-CLPTM1L locus is associated with estrogen receptor–negative breast cancer 
Haiman, Christopher A | Chen, Gary K | Vachon, Celine M | Canzian, Federico | Dunning, Alison | Millikan, Robert C | Wang, Xianshu | Ademuyiwa, Foluso | Ahmed, Shahana | Ambrosone, Christine B | Baglietto, Laura | Balleine, Rosemary | Bandera, Elisa V | Beckmann, Matthias W | Berg, Christine D | Bernstein, Leslie | Blomqvist, Carl | Blot, William J | Brauch, Hiltrud | Buring, Julie E | Carey, Lisa A | Carpenter, Jane E | Chang-Claude, Jenny | Chanock, Stephen J | Chasman, Daniel I | Clarke, Christine L | Cox, Angela | Cross, Simon S | Deming, Sandra L | Diasio, Robert B | Dimopoulos, Athanasios M | Driver, W Ryan | Dünnebier, Thomas | Durcan, Lorraine | Eccles, Diana | Edlund, Christopher K | Ekici, Arif B | Fasching, Peter A | Feigelson, Heather S | Flesch-Janys, Dieter | Fostira, Florentia | Försti, Asta | Fountzilas, George | Gerty, Susan M | Giles, Graham G | Godwin, Andrew K | Goodfellow, Paul | Graham, Nikki | Greco, Dario | Hamann, Ute | Hankinson, Susan E | Hartmann, Arndt | Hein, Rebecca | Heinz, Judith | Holbrook, Andrea | Hoover, Robert N | Hu, Jennifer J | Hunter, David J | Ingles, Sue A | Irwanto, Astrid | Ivanovich, Jennifer | John, Esther M | Johnson, Nicola | Jukkola-Vuorinen, Arja | Kaaks, Rudolf | Ko, Yon-Dschun | Kolonel, Laurence N | Konstantopoulou, Irene | Kosma, Veli-Matti | Kulkarni, Swati | Lambrechts, Diether | Lee, Adam M | Le Marchand, Loïc | Lesnick, Timothy | Liu, Jianjun | Lindstrom, Sara | Mannermaa, Arto | Margolin, Sara | Martin, Nicholas G | Miron, Penelope | Montgomery, Grant W | Nevanlinna, Heli | Nickels, Stephan | Nyante, Sarah | Olswold, Curtis | Palmer, Julie | Pathak, Harsh | Pectasides, Dimitrios | Perou, Charles M | Peto, Julian | Pharoah, Paul D P | Pooler, Loreall C | Press, Michael F | Pylkäs, Katri | Rebbeck, Timothy R | Rodriguez-Gil, Jorge L | Rosenberg, Lynn | Ross, Eric | Rüdiger, Thomas | Silva, Isabel dos Santos | Sawyer, Elinor | Schmidt, Marjanka K | Schulz-Wendtland, Rüdiger | Schumacher, Fredrick | Severi, Gianluca | Sheng, Xin | Signorello, Lisa B | Sinn, Hans-Peter | Stevens, Kristen N | Southey, Melissa C | Tapper, William J | Tomlinson, Ian | Hogervorst, Frans B L | Wauters, Els | Weaver, JoEllen | Wildiers, Hans | Winqvist, Robert | Van Den Berg, David | Wan, Peggy | Xia, Lucy Y | Yannoukakos, Drakoulis | Zheng, Wei | Ziegler, Regina G | Siddiq, Afshan | Slager, Susan L | Stram, Daniel O | Easton, Douglas | Kraft, Peter | Henderson, Brian E | Couch, Fergus J
Nature Genetics  2011;43(12):1210-1214.
Estrogen receptor (ER)-negative breast cancer shows a higher incidence in women of African ancestry compared to women of European ancestry. In search of common risk alleles for ER-negative breast cancer, we combined genome-wide association study (GWAS) data from women of African ancestry (1,004 ER-negative cases and 2,745 controls) and European ancestry (1,718 ER-negative cases and 3,670 controls), with replication testing conducted in an additional 2,292 ER-negative cases and 16,901 controls of European ancestry. We identified a common risk variant for ER-negative breast cancer at the TERT-CLPTM1L locus on chromosome 5p15 (rs10069690: per-allele odds ratio (OR) = 1.18 per allele, P = 1.0 × 10−10). The variant was also significantly associated with triple-negative (ER-negative, progesterone receptor (PR)-negative and human epidermal growth factor-2 (HER2)-negative) breast cancer (OR = 1.25, P = 1.1 × 10−9), particularly in younger women (<50 years of age) (OR = 1.48, P = 1.9 × 10−9). Our results identify a genetic locus associated with estrogen receptor negative breast cancer subtypes in multiple populations.
doi:10.1038/ng.985
PMCID: PMC3279120  PMID: 22037553

Results 1-25 (57)