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New ML, Hirsch EA, Feser WJ, Malkoski SP, Garg K, Miller YE, Baron AE. Differences in VA and non-VA pulmonary nodules: All evaluations are not created equal. Clin Lung Cancer 2023:S1525-7304(23)00037-2. [PMID: 37012147 DOI: 10.1016/j.cllc.2023.02.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 02/06/2023] [Accepted: 02/10/2023] [Indexed: 03/07/2023]
Abstract
BACKGROUND Indeterminate pulmonary nodules present a common challenge for clinicians who must recommend surveillance or intervention based on an assessed risk of malignancy. PATIENTS AND METHODS In this cohort study, patients presenting for indeterminate pulmonary nodule evaluation were enrolled at sites participating in the Colorado SPORE in Lung Cancer. They were followed prospectively and included for analysis if they had a definitive malignant diagnosis, benign diagnosis, or radiographic resolution or stability of their nodule for > 2 years. RESULTS Patients evaluated at the Veterans Affairs (VA) and non-VA sites were equally as likely to have a malignant diagnosis (48%). The VA cohort represented a higher-risk group than the non-VA cohort regarding smoking history and chronic obstructive pulmonary disease (COPD). There were more squamous cell carcinoma diagnoses among VA malignant nodules (25% vs. 10%) and a later stage at diagnosis among VA patients. Discrimination and calibration of risk calculators produced estimates that were wide-ranging and different when comparing between risk score calculators as well as between VA/non-VA cohorts. Application of current American College of Chest Physicians guidelines to our groups could have resulted in inappropriate resection of 12% of benign nodules. CONCLUSION Comparison of VA with non-VA patients shows important differences in underlying risk, histology of malignant nodules, and stage at diagnosis. This study highlights the challenge in applying risk calculators to a clinical setting, as the model discrimination and calibration were variable between calculators and between our higher-risk VA and lower-risk non-VA groups. MICROABSTRACT Risk stratification and management of indeterminate pulmonary nodules (IPNs) is a common clinical problem. In this prospective cohort study of 282 patients with IPNs from Veterans Affairs (VA) and non-VA sites, we found differences in patient and nodule characteristics, histology and diagnostic stage, and risk calculator performance. Our findings highlight challenges and shortcomings of current IPN management guidelines and tools.
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Kammer MN, Lakhani DA, Balar AB, Antic SL, Kussrow AK, Webster RL, Mahapatra S, Barad U, Shah C, Atwater T, Diergaarde B, Qian J, Kaizer A, New M, Hirsch E, Feser WJ, Strong J, Rioth M, Miller YE, Balagurunathan Y, Rowe DJ, Helmey S, Chen SC, Bauza J, Deppen SA, Sandler K, Maldonado F, Spira A, Billatos E, Schabath MB, Gillies RJ, Wilson DO, Walker RC, Landman B, Chen H, Grogan EL, Barón AE, Bornhop DJ, Massion PP. Integrated Biomarkers for the Management of Indeterminate Pulmonary Nodules. Am J Respir Crit Care Med 2021; 204:1306-1316. [PMID: 34464235 PMCID: PMC8786067 DOI: 10.1164/rccm.202012-4438oc] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 08/27/2021] [Indexed: 01/06/2023] Open
Abstract
Rationale: Patients with indeterminate pulmonary nodules (IPNs) at risk of cancer undergo high rates of invasive, costly, and morbid procedures. Objectives: To train and externally validate a risk prediction model that combined clinical, blood, and imaging biomarkers to improve the noninvasive management of IPNs. Methods: In this prospectively collected, retrospective blinded evaluation study, probability of cancer was calculated for 456 patient nodules using the Mayo Clinic model, and patients were categorized into low-, intermediate-, and high-risk groups. A combined biomarker model (CBM) including clinical variables, serum high sensitivity CYFRA 21-1 level, and a radiomic signature was trained in cohort 1 (n = 170) and validated in cohorts 2-4 (total n = 286). All patients were pooled to recalibrate the model for clinical implementation. The clinical utility of the CBM compared with current clinical care was evaluated in 2 cohorts. Measurements and Main Results: The CBM provided improved diagnostic accuracy over the Mayo Clinic model with an improvement in area under the curve of 0.124 (95% bootstrap confidence interval, 0.091-0.156; P < 2 × 10-16). Applying 10% and 70% risk thresholds resulted in a bias-corrected clinical reclassification index for cases and control subjects of 0.15 and 0.12, respectively. A clinical utility analysis of patient medical records estimated that a CBM-guided strategy would have reduced invasive procedures from 62.9% to 50.6% in the intermediate-risk benign population and shortened the median time to diagnosis of cancer from 60 to 21 days in intermediate-risk cancers. Conclusions: Integration of clinical, blood, and image biomarkers improves noninvasive diagnosis of patients with IPNs, potentially reducing the rate of unnecessary invasive procedures while shortening the time to diagnosis.
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Affiliation(s)
- Michael N. Kammer
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine
- Department of Chemistry, and
| | - Dhairya A. Lakhani
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine
| | - Aneri B. Balar
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine
| | - Sanja L. Antic
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine
| | - Amanda K. Kussrow
- Department of Chemistry, and
- Vanderbilt Institute for Chemical Biology, Nashville, Tennessee
- Vanderbilt Ingram Cancer Center, Nashville, Tennessee
| | | | - Shayan Mahapatra
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine
| | | | | | - Thomas Atwater
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine
| | - Brenda Diergaarde
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh and UPMC Hillman Cancer Center, Pittsburgh, Pennsylvania
| | - Jun Qian
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine
| | - Alexander Kaizer
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | | | - Erin Hirsch
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - William J. Feser
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Jolene Strong
- Biomedical Informatics and Personalized Medicine, and
| | - Matthew Rioth
- Medical Oncology and Biomedical Informatics and Personalized Medicine, School of Medicine, University of Colorado, Aurora, Colorado
| | | | | | - Dianna J. Rowe
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine
| | - Sherif Helmey
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine
| | - Sheau-Chiann Chen
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Joseph Bauza
- American College of Radiology, Philadelphia, Pennsylvania
| | - Stephen A. Deppen
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine
| | - Kim Sandler
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine
| | - Fabien Maldonado
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine
| | - Avrum Spira
- Department of Medicine, Boston University, Boston, Massachusetts
| | - Ehab Billatos
- Department of Medicine, Boston University, Boston, Massachusetts
| | | | | | - David O. Wilson
- Department of Medicine, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania; and
| | | | - Bennett Landman
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
| | - Heidi Chen
- American College of Radiology, Philadelphia, Pennsylvania
| | - Eric L. Grogan
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine
| | - Anna E. Barón
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Darryl J. Bornhop
- Department of Chemistry, and
- Vanderbilt Institute for Chemical Biology, Nashville, Tennessee
- Vanderbilt Ingram Cancer Center, Nashville, Tennessee
| | - Pierre P. Massion
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine
- Vanderbilt Ingram Cancer Center, Nashville, Tennessee
- Pulmonary Section, Medical Service, Tennessee Valley Healthcare Systems Nashville Campus, Nashville, Tennessee
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Donovan LM, Palen BN, Syed A, Blankenhorn R, Blanchard K, Feser WJ, Magid K, Gamache J, Spece LJ, Feemster LC, Fernandes L, Kirsh S, Au DH. Nurse-led triage of new sleep referrals is associated with lower risk of potentially contraindicated sleep testing: a retrospective cohort study. BMJ Qual Saf 2020; 30:599-607. [PMID: 33443226 DOI: 10.1136/bmjqs-2020-011817] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 11/21/2020] [Accepted: 12/01/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND The volume of specialty care referrals often outstrips specialists' capacity. The Department of Veterans Affairs launched a system of referral coordination to augment our workforce, empowering registered nurses to use decision support tools to triage specialty referrals. While task shifting may improve access, there is limited evidence regarding the relative quality of nurses' triage decisions to ensure such management is safe. OBJECTIVE Within the specialty of sleep medicine, we compared receipt of contraindicated testing for obstructive sleep apnoea (OSA) between patients triaged to sleep testing by nurses in the referral coordination system (RCS) relative to our traditional specialist-led system (TSS). METHODS Patients referred for OSA evaluation can be triaged to either home sleep apnoea testing (HSAT) or polysomnography, and existing guidelines specify patients for whom HSAT is contraindicated. In RCS, nurses used a decision support tool to make triage decisions for sleep testing but were instructed to seek specialist oversight in complex cases. In TSS, specialists made triage decisions themselves. We performed a single-centre retrospective cohort study of patients without OSA who were referred to sleep testing between September 2018 and August 2019. Patients were assigned to triage by RCS or TSS in quasirandom fashion based on triager availability at time of referral. We compared receipt of contraindicated sleep tests between groups using a generalised linear model adjusted for day of the week and time of day of referral. RESULTS RCS triaged 793 referrals for OSA evaluation relative to 1787 by TSS. Patients with RCS triages were at lower risk of receiving potentially contraindicated sleep tests relative risk 0.52 (95% CI 0.29 to 0.93). CONCLUSION Our results suggest that incorporating registered nurses into triage decision-making may improve the quality of diagnostic care for OSA.
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Affiliation(s)
- Lucas M Donovan
- Health Services Research and Development, VA Puget Sound Health Care System, Seattle, Washington, USA .,Department of Pulmonary, Critical Care, and Sleep Medicine, VA Puget Sound Health Care System and University of Washington, Seattle, Washington, USA
| | - Brian N Palen
- Department of Pulmonary, Critical Care, and Sleep Medicine, VA Puget Sound Health Care System and University of Washington, Seattle, Washington, USA
| | - Adnan Syed
- VA HSR&D Center of Innovation for Veteran-Centered and Value-Driven Care, VA Eastern Colorado Health Care System, Aurora, Colorado, USA
| | - Richard Blankenhorn
- VA HSR&D Center of Innovation for Veteran-Centered and Value-Driven Care, VA Eastern Colorado Health Care System, Aurora, Colorado, USA
| | - Kelly Blanchard
- VA HSR&D Center of Innovation for Veteran-Centered and Value-Driven Care, VA Eastern Colorado Health Care System, Aurora, Colorado, USA
| | - William J Feser
- VA HSR&D Center of Innovation for Veteran-Centered and Value-Driven Care, VA Eastern Colorado Health Care System, Aurora, Colorado, USA
| | - Kate Magid
- VA HSR&D Center of Innovation for Veteran-Centered and Value-Driven Care, VA Eastern Colorado Health Care System, Aurora, Colorado, USA
| | - Justina Gamache
- Department of Pulmonary, Critical Care, and Sleep Medicine, VA Puget Sound Health Care System and University of Washington, Seattle, Washington, USA
| | - Laura J Spece
- Health Services Research and Development, VA Puget Sound Health Care System, Seattle, Washington, USA.,Department of Pulmonary, Critical Care, and Sleep Medicine, VA Puget Sound Health Care System and University of Washington, Seattle, Washington, USA
| | - Laura C Feemster
- Health Services Research and Development, VA Puget Sound Health Care System, Seattle, Washington, USA.,Department of Pulmonary, Critical Care, and Sleep Medicine, VA Puget Sound Health Care System and University of Washington, Seattle, Washington, USA
| | | | - Susan Kirsh
- Office of Veterans Access to Care, Department of Veterans Affairs, Washington, DC, USA
| | - David H Au
- Health Services Research and Development, VA Puget Sound Health Care System, Seattle, Washington, USA.,Department of Pulmonary, Critical Care, and Sleep Medicine, VA Puget Sound Health Care System and University of Washington, Seattle, Washington, USA
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Warsavage T, Xing F, Barón AE, Feser WJ, Hirsch E, Miller YE, Malkoski S, Wolf HJ, Wilson DO, Ghosh D. Quantifying the incremental value of deep learning: Application to lung nodule detection. PLoS One 2020; 15:e0231468. [PMID: 32287288 PMCID: PMC7156089 DOI: 10.1371/journal.pone.0231468] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Accepted: 03/24/2020] [Indexed: 12/23/2022] Open
Abstract
We present a case study for implementing a machine learning algorithm with an incremental value framework in the domain of lung cancer research. Machine learning methods have often been shown to be competitive with prediction models in some domains; however, implementation of these methods is in early development. Often these methods are only directly compared to existing methods; here we present a framework for assessing the value of a machine learning model by assessing the incremental value. We developed a machine learning model to identify and classify lung nodules and assessed the incremental value added to existing risk prediction models. Multiple external datasets were used for validation. We found that our image model, trained on a dataset from The Cancer Imaging Archive (TCIA), improves upon existing models that are restricted to patient characteristics, but it was inconclusive about whether it improves on models that consider nodule features. Another interesting finding is the variable performance on different datasets, suggesting population generalization with machine learning models may be more challenging than is often considered.
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Affiliation(s)
- Theodore Warsavage
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
| | - Fuyong Xing
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
| | - Anna E. Barón
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
| | - William J. Feser
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
| | - Erin Hirsch
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
| | - York E. Miller
- Department of Pulmonary Sciences and Critical Care Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
- Rocky Mountain Regional Veterans Affairs Medical Center, Aurora, CO, United States of America
| | - Stephen Malkoski
- Department of Pulmonary and Critical Care Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
| | - Holly J. Wolf
- Department of Community and Behavioral Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
| | - David O. Wilson
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Debashis Ghosh
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
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5
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Barón AE, Kako S, Feser WJ, Malinowski H, Merrick D, Garg K, Malkoski S, Pretzel S, Siegfried JM, Franklin WA, Miller Y, Wolf HJ, Varella-Garcia M. Clinical Utility of Chromosomal Aneusomy in Individuals at High Risk of Lung Cancer. J Thorac Oncol 2017. [PMID: 28634123 DOI: 10.1016/j.jtho.2017.06.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
INTRODUCTION Low-dose computed tomography screening for lung cancer has a high false-positive rate with frequent discovery of indeterminate pulmonary nodules. Noninvasive biomarkers are needed to reduce false positives and improve risk stratification. A retrospective longitudinal evaluation was performed to assess chromosomal aneusomy in sputum by fluorescence in situ hybridization (CA-FISH) in four nested case-control studies. METHODS Receiver operating characteristic analysis resulted in two grouped cohorts: a high-risk cohort (Colorado High-Risk Cohort and Colorado Nodule Cohort [68 case patients and 69 controls]) and a screening cohort (American College of Radiology Imaging Network/National Lung Screening Trial and Pittsburgh Lung Screening Study [97 case patients and 185 controls]). The CA-FISH assay was a four-target DNA panel encompassing the EGFR and v-myc avian myelocytomatosis viral oncogene homolog (MYC) genes, and the 5p15 and centromere 6 regions or the fibroblast growth factor 1 gene (FGFR1) and phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha gene (PIK3CA). A four-category scale (normal, probably normal, probably abnormal, and abnormal) was applied. Sensitivity, specificity, and positive and negative likelihood ratios (LRs) (with 95% confidence intervals [CIs]) were estimated for each cohort. RESULTS Sensitivity and specificity were, respectively, 0.67 (95% CI: 0.55-0.78) and 0.94 (95% CI: 0.85-0.98) for high-risk participants and 0.20 (95% CI: 0.13-0.30) and 0.84 (95% CI: 0.78-0.89) for screening participants. The positive and negative LRs were, respectively, 11.66 (95% CI: 4.44-30.63) and 0.34 (95% CI: 0.24-0.48) for high-risk participants and 1.36 (95% CI: 0.81-2.28) and 0.93 (95% CI: 0.83-1.05) for screening participants. CONCLUSION The high positive LR of sputum CA-FISH indicates that it could be a useful adjunct to low-dose computed tomography for lung cancer in high-risk settings. For screening, however, its low positive LR limits clinical utility. Prospective assessment of CA-FISH in the incidentally identified indeterminate nodule setting is ongoing in the Colorado Pulmonary Nodule Biomarker Trial.
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Affiliation(s)
- Anna E Barón
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado.
| | - Severine Kako
- Department of Medicine, Division of Medical Oncology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado; Department of Pathology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - William J Feser
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Heather Malinowski
- Department of Pathology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Daniel Merrick
- Department of Pathology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Kavita Garg
- Department of Radiology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Stephen Malkoski
- Department of Pulmonary and Critical Care Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Shannon Pretzel
- University of Colorado Cancer Center, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Jill M Siegfried
- Department of Pharmacology, Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota; Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Wilbur A Franklin
- Department of Pathology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - York Miller
- Department of Pulmonary and Critical Care Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado; Veterans Affairs Medical Center, Denver, Colorado
| | - Holly J Wolf
- Department of Community and Behavioral Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado
| | - Marileila Varella-Garcia
- Department of Medicine, Division of Medical Oncology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado; Department of Pathology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado
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Sedjo RL, Hines LM, Byers T, Giuliano AR, Marcus A, Vadaparampil S, Jacobsen P, Kilbourn K, Feser WJ, Risendal BC. Long-term weight gain among Hispanic and non-Hispanic White women with and without breast cancer. Nutr Cancer 2013; 65:34-42. [PMID: 23368911 DOI: 10.1080/01635581.2013.741750] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
Weight gain following breast cancer diagnosis is common, but limited data exists on whether this gain is in excess of that gained during normal aging. This study investigated weight patterns among women with and without breast cancer to determine the effects of the breast cancer experience on weight change. Using the SHINE 4-Corners Breast Cancer Study, 305 women with breast cancer and 345 women without were followed prospectively. Weight change of ≥5% was defined as the difference between the self-reported weight measurements obtained at breast cancer diagnosis (or referent date for women without breast cancer) and about 6 yr later. Multiple logistic regression analyses were used. Within this cohort, 60% of women were overweight or obese and 37% of women gained weight. No significant greater weight gain was observed between women with vs. without breast cancer [adjusted odds ratio (ORadj) = 1.15, 95% CI 0.79-1.68] or between Hispanic vs. non-Hispanic White women (ORadj = 1.09, 95% CI 0.72-1.66) after adjustment. Weight gain was associated with being younger and having a lower body mass index. Among breast cancer survivors, cancer treatment factors were not associated with weight gain. These results suggest that weight management approaches are needed, especially those targeted to at-risk populations such as breast cancer survivors.
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Affiliation(s)
- Rebecca L Sedjo
- Department of Community and Behavioral Health, Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado 80045, USA
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Mascaux C, Feser WJ, Lewis MT, Barón AE, Coldren CD, Merrick DT, Kennedy TC, Eckelberger JI, Rozeboom LM, Franklin WA, Minna JD, Bunn PA, Miller YE, Keith RL, Hirsch FR. Endobronchial miRNAs as biomarkers in lung cancer chemoprevention. Cancer Prev Res (Phila) 2013; 6:100-8. [PMID: 23268837 PMCID: PMC4159305 DOI: 10.1158/1940-6207.capr-12-0382] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Lung cancers express lower levels of prostacyclin than normal lung tissues. Prostacyclin prevents lung cancer in a variety of mouse models. A randomized phase II trial comparing oral iloprost (a prostacyclin analog) with placebo in high-risk subjects showed improvement in bronchial histology in former, but not current, smokers. This placebo-controlled study offered the opportunity for investigation of other potential intermediate endpoint and predictive biomarkers to incorporate into chemoprevention trials. Matched bronchial biopsies were obtained at baseline and at 6-month follow-up from 125 high-risk individuals who completed the trial: 31/29 and 37/28 current/former smokers in the iloprost and placebo arm, respectively. We analyzed the expression of 14 selected miRNAs by Real Time PCR in 496 biopsies. The expression of seven miRNAs was significantly correlated with histology at baseline. The expression of miR-34c was inversely correlated with histology at baseline (P < 0.0001) and with change in histology at follow-up (P = 0.0003), independent of treatment or smoking status. Several miRNAs were also found to be differentially expressed in current smokers as compared with former smokers. In current smokers, miR-375 was upregulated at baseline (P < 0.0001) and downregulated after treatment with iloprost (P = 0.0023). No miRNA at baseline reliably predicted a response to iloprost. No biomarker predictive of response to iloprost was found. MiR-34c was inversely correlated with baseline histology and with histology changes. Mir-34c changes at follow-up could be used as a quantitative biomarker that parallels histologic response in formalin-fixed bronchial biopsies in future lung cancer chemoprevention studies.
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Affiliation(s)
- Celine Mascaux
- Department of Medicine, Division of Medical Oncology, Colorado School of Public Health, Aurora, 80045, USA.
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8
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Leng S, Do K, Yingling CM, Picchi MA, Wolf HJ, Kennedy TC, Feser WJ, Baron AE, Franklin WA, Brock MV, Herman JG, Baylin SB, Byers T, Stidley CA, Belinsky SA. Defining a gene promoter methylation signature in sputum for lung cancer risk assessment. Clin Cancer Res 2012; 18:3387-95. [PMID: 22510351 PMCID: PMC3483793 DOI: 10.1158/1078-0432.ccr-11-3049] [Citation(s) in RCA: 81] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
PURPOSE To evaluate the methylation state of 31 genes in sputum as biomarkers in an expanded nested, case-control study from the Colorado cohort, and to assess the replication of results from the most promising genes in an independent case-control study of asymptomatic patients with stage I lung cancer from New Mexico. EXPERIMENTAL DESIGN Cases and controls from Colorado and New Mexico were interrogated for methylation of up to 31 genes using nested, methylation-specific PCR. Individual genes and methylation indices were used to assess the association between methylation and lung cancer with logistic regression modeling. RESULTS Seventeen genes with ORs of 1.4 to 3.6 were identified and selected for replication in the New Mexico study. Overall, the direction of effects seen in New Mexico was similar to Colorado with the largest increase in case discrimination (ORs, 3.2-4.2) seen for the PAX5α, GATA5, and SULF2 genes. Receiver operating characteristic (ROC) curves generated from seven-gene panels from Colorado and New Mexico studies showed prediction accuracy of 71% and 77%, respectively. A 22-fold increase in lung cancer risk was seen for a subset of New Mexico cases with five or more genes methylated. Sequence variants associated with lung cancer did not improve the accuracy of this gene methylation panel. CONCLUSIONS These studies have identified and replicated a panel of methylated genes whose integration with other promising biomarkers could initially identify the highest risk smokers for computed tomographic screening for early detection of lung cancer.
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Affiliation(s)
- Shuguang Leng
- Lung Cancer Program, Lovelace Respiratory Research Institute, Department of Internal Medicine, University of New Mexico, Albuquerque, New Mexico 87108, USA
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Malkoski SP, Haeger SM, Cleaver TG, Rodriguez KJ, Li H, Lu SL, Feser WJ, Barón AE, Merrick D, Lighthall JG, Ijichi H, Franklin W, Wang XJ. Loss of transforming growth factor beta type II receptor increases aggressive tumor behavior and reduces survival in lung adenocarcinoma and squamous cell carcinoma. Clin Cancer Res 2012; 18:2173-83. [PMID: 22399565 DOI: 10.1158/1078-0432.ccr-11-2557] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
PURPOSE Lung adenocarcinoma and lung squamous cell carcinoma (SCC) are the most common non-small cell lung cancer (NSCLC) subtypes. This study was designed to determine whether reduced expression of TGFβ type II receptor (TGFβRII) promotes lung adenocarcinoma and SCC carcinogenesis. EXPERIMENTAL DESIGN We examined TGFβRII expression at the protein and mRNA levels in human NSCLC samples and assessed the relationship between TGFβRII expression and clinicopathologic parameters. To determine whether sporadic TGFβRII deletion in airway epithelial cells induces NSCLC formation, we targeted TGFβRII deletion alone and in combination with oncogenic Kras(G12D) to murine airways using a keratin 5 (K5) promoter and inducible Cre recombinase. RESULTS Reduced TGFβRII expression in human NSCLC is associated with male gender, smoking, SCC histology, reduced differentiation, increased tumor stage, increased nodal metastasis, and reduced survival. Homozygous or heterozygous TGFβRII deletion in mouse airway epithelia increases the size and number of Kras(G12D)-initiated adenocarcinoma and SCC. TGFβRII deletion increases proliferation, local inflammation, and TGFβ ligand elaboration; TGFβRII knockdown in airway epithelial cells increases migration and invasion. CONCLUSIONS Reduced TGFβRII expression in human NSCLC is associated with more aggressive tumor behavior and inflammation that is, at least partially, mediated by increased TGFβ1 expression. TGFβRII deletion in mouse airway epithelial cells promotes adenocarcinoma and SCC formation, indicating that TGFβRII loss plays a causal role in lung carcinogenesis. That TGFβRII shows haploid insufficiency suggests that a 50% TGFβRII protein reduction would negatively impact lung cancer prognosis.
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Affiliation(s)
- Stephen P Malkoski
- Division of Pulmonary Sciences and Critical Care Medicine, Department of Pathology, Colorado School of Public Health, University of Colorado Denver Anschutz Medical Campus, Aurora, Colorado, USA
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Mascaux C, Keith RL, Feser WJ, Lewis MT, Baron AE, Coldren CD, Merrick DT, Kennedy TC, Eckelberger JI, Franklin WA, Bunn PA, Miller YE, Hirsch FR. Abstract B16: Histology and intervention related miRNA expression changes from baseline to follow-up paired bronchial biopsies of patient in the iloprost chemoprevention trial. Clin Cancer Res 2012. [DOI: 10.1158/1078-0432.12aacriaslc-b16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
The iloprost lung cancer chemoprevention trial is the first to meet a primary endpoint of improvement in endobronchial histology, which is currently considered to be the best intermediate endpoint for chemoprevention (Keith et al, Cancer Prev Res, 2011). This placebo-controlled study offers the opportunity for discovering other surrogate endpoints and predictive biomarkers to incorporate into chemoprevention trials.
We compared miRNA expression in follow-up (FU) versus baseline biopsies in relation with histology change or not globally and stratified by treatment arm and smoking status.
In the 152 patients randomized in the iloprost trial, the paired baseline and FU biopsies were available in 125 patients: 40/35 current/former smokers in the iloprost arm and 25/25 current/former smokers in the placebo arm, respectively. We planned to analyze 500 biopsies: four biopsies from each of the 125 patients, 2 biopsies at baseline (worst and best diagnosis) and 2 biopsies at FU at the same site after six months of treatment with iloprost or placebo. We selected and analyzed 14 miRNAs differentially expressed during squamous cell lung carcinogenesis in our previous study (Mascaux et al, Eur Resp J, 2009).
In total, 496/500 biopsies with appropriate tissue were available. For every biopsy, total RNA was extracted from 8 adjacent 4 um cuts of formalin fixed paraffin embedded (FFPE) adjacent to the diagnostic section. A good reproducibility of the previously published data for the expression changes in the 14 miRNA accross lung preneoplasia stages was shown in the current study in baseline samples. This new study identifies significant changes in miR-34c expression between paired samples when histology is up- or downgraded. miR-34c is significantly down-regulated in paired biopsies when histology is up-graded and inversely. This correlation between miR-34c expression and histology changes is shown including all samples (r spearman correlation=0.23 p=0.0003), but also consistently in subgroups (iloprost.arm, current r=0.26, p=0.041 and former smokers r=0.24, p=0.066, placebo arm, current (r=0.23, p=0.046)). In contrast, miR-9 was significantly down-regulated in follow-up as compared with baseline biopsies, but was not correlated with histology changes. The down-regulation of miR-9 in follow-up versus baseline samples was found in all samples (t test, p<0.0001) and was consistent in all and significant in most of subgroups (iloprost arm, all patients (p=0.0007) and current smokers (p=0.0023) and placebo arm, all patients (p=0.001), current smokers (p=0.047) and former smokers (p=0.0071).
In conclusion, miR-34c, a transcriptional target of p53 which is down-regulated by hypermethylation in lung cancer, is down-regulated when histology changes from the normal bronchial mucosa to high-grade bronchial lesions, and inversely, independently of treatment and smoking status. miR-34c expression is a good reflection of baseline histology and histology changes. Alternatively, miR-9 is systematically down-regulated in follow-up biopsies 6 months later at the same site independently of histology, treatment and tobacco status. This suggests that the down-regulation of miR-9 in the follow-up samples may be related to the biopsy: this miRNA could be involved in the tissue repair.
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Rafnar T, Sulem P, Besenbacher S, Gudbjartsson DF, Zanon C, Gudmundsson J, Stacey SN, Kostic JP, Thorgeirsson TE, Thorleifsson G, Bjarnason H, Skuladottir H, Gudbjartsson T, Isaksson HJ, Isla D, Murillo L, García-Prats MD, Panadero A, Aben KKH, Vermeulen SH, van der Heijden HFM, Feser WJ, Miller YE, Bunn PA, Kong A, Wolf HJ, Franklin WA, Mayordomo JI, Kiemeney LA, Jonsson S, Thorsteinsdottir U, Stefansson K. Genome-wide significant association between a sequence variant at 15q15.2 and lung cancer risk. Cancer Res 2011; 71:1356-61. [PMID: 21303977 DOI: 10.1158/0008-5472.can-10-2852] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Genome-wide association studies (GWAS) have identified 3 genomic regions, at 15q24-25.1, 5p15.33, and 6p21.33, which associate with the risk of lung cancer. Large meta-analyses of GWA data have failed to find additional associations of genome-wide significance. In this study, we sought to confirm 7 variants with suggestive association to lung cancer (P < 10(-5)) in a recently published meta-analysis. In a GWA dataset of 1,447 lung cancer cases and 36,256 controls in Iceland, 3 correlated variants on 15q15.2 (rs504417, rs11853991, and rs748404) showed a significant association with lung cancer, whereas rs4254535 on 2p14, rs1530057 on 3p24.1, rs6438347 on 3q13.31, and rs1926203 on 10q23.31 did not. The most significant variant, rs748404, was genotyped in an additional 1,299 lung cancer cases and 4,102 controls from the Netherlands, Spain, and the United States and the results combined with published GWAS data. In this analysis, the T allele of rs748404 reached genome-wide significance (OR = 1.15, P = 1.1 × 10(-9)). Another variant at the same locus, rs12050604, showed association with lung cancer (OR = 1.09, 3.6 × 10(-6)) and remained significant after adjustment for rs748404 and vice versa. rs748404 is located 140 kb centromeric of the TP53BP1 gene that has been implicated in lung cancer risk. Two fully correlated, nonsynonymous coding variants in TP53BP1, rs2602141 (Q1136K) and rs560191 (E353D) showed association with lung cancer in our sample set; however, this association did not remain significant after adjustment for rs748404. Our data show that 1 or more lung cancer risk variants of genome-wide significance and distinct from the coding variants in TP53BP1 are located at 15q15.2.
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Affiliation(s)
- Thorunn Rafnar
- deCODE genetics, Department of Medical Oncology, Landspitali-University Hospital, Faculty of Medicine, University of Iceland, Reykjavik, Iceland
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Varella-Garcia M, Schulte AP, Wolf HJ, Feser WJ, Zeng C, Braudrick S, Yin X, Hirsch FR, Kennedy TC, Keith RL, Barón AE, Belinsky SA, Miller YE, Byers T, Franklin WA. The detection of chromosomal aneusomy by fluorescence in situ hybridization in sputum predicts lung cancer incidence. Cancer Prev Res (Phila) 2010; 3:447-53. [PMID: 20332298 DOI: 10.1158/1940-6207.capr-09-0165] [Citation(s) in RCA: 41] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Lung cancer usually is disseminated (advanced) and has a poor prognosis at diagnosis. Current and former smokers are at a high risk for lung cancer and are candidates for prevention and early detection strategies. Sputum is a potential source of biomarkers that might determine either lung cancer risk or the presence of early lung cancer, but no current sputum test is sufficiently sensitive and specific for effective screening. We used fluorescence in situ hybridization (FISH) to measure chromosomal aneusomy (CA) in sputum samples collected prospectively from 100 incident lung cancer cases and 96 controls (matched on age, gender, and date of collection) nested within an ongoing high-risk cohort. The CA-FISH assay was aimed at four DNA targets: epidermal growth factor receptor, MYC, 5p15, and CEP 6. The sensitivity of a positive CA-FISH assay (abnormal for two or more of the four markers) for lung cancer was substantially higher for samples collected within 18 months (76% sensitivity) than for samples collected more than 18 months (31%) before lung cancer diagnosis. Sensitivity was higher for squamous cell cancers (94%) than for other histologic types (69%). CA-FISH specificity based on samples collected within 18 months before diagnosis was 88%. The adjusted odds ratio (OR) of lung cancer for specimens collected within 18 months before a cancer diagnosis was higher for the CA-FISH assay [OR, 29.9; 95% confidence interval (95% CI), 9.5-94.1] than for previously studied ORs of cytologic atypia (OR, 1.8; 95% CI, 1.3-2.6) and gene promoter methylation (OR, 6.5; 95% CI, 1.2-35.5). Whether CA-FISH is an indicator of extreme risk for incident lung cancer or detects exfoliated cancer cells is unknown. The apparent promise of CA-FISH in sputum for assessing lung cancer risk and/or for lung cancer early detection now needs to be validated in a clinical screening trial.
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Feser WJ, Fingerlin TE, Strand MJ, Glueck DH. CALCULATING AVERAGE POWER FOR THE BENJAMINI-HOCHBERG PROCEDURE. J Stat Theory Appl 2009; 8:325-352. [PMID: 27818616 PMCID: PMC5095931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2023] Open
Abstract
Using exact, analytic results for the average power of the Benjamini-Hochberg (1995) procedure, we provide example power analyses useful for scientists planning studies involving multiple comparisons. The power results are based on the distribution of the p-value under the alternative for the Pearson's χ2, and for the Hotelling-Lawley trace, the Wilks' lambda, and the Pillai-Bartlett trace, all tests for the general linear multivariate model. Detailed example power analyses are given for a planned mammography experiment with categorical data and a study that tests the association of a single nucleotide polymorphism with insulin resistance and visceral adiposity.
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Affiliation(s)
- William J. Feser
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Denver
- A portion of the work reported here was completed in partial fulfillment of the requirements for the Masters degree in Biostatistics from the University of Colorado Denver
| | - Tasha E. Fingerlin
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Denver
| | | | - Deborah H. Glueck
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Denver
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