Martin C. Tammemagi

Probability of Cancer in Pulmonary Nodules Detected on First Screening CT

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.).

Overdiagnosis in Low-Dose Computed Tomography Screening for Lung Cancer

IMPORTANCE Screening for lung cancer has the potential to reduce mortality, but in addition to detecting aggressive tumors, screening will also detect indolent tumors that otherwise may not cause clinical symptoms. These overdiagnosis cases represent an important potential harm of screening because they incur additional cost, anxiety, and morbidity associated with cancer treatment. OBJECTIVE To estimate overdiagnosis in the National Lung Screening Trial (NLST). DESIGN, SETTING, AND PARTICIPANTS We used data from the NLST, a randomized trial comparing screening using low-dose computed tomography (LDCT) vs chest radiography (CXR) among 53 452 persons at high risk for lung cancer observed for 6.4 years, to estimate the excess number of lung cancers in the LDCT arm of the NLST compared with the CXR arm. MAIN OUTCOMES AND MEASURES We calculated 2 measures of overdiagnosis: the probability that a lung cancer detected by screening with LDCT is an overdiagnosis (PS), defined as the excess lung cancers detected by LDCT divided by all lung cancers detected by screening in the LDCT arm; and the number of cases that were considered overdiagnosis relative to the number of persons needed to screen to prevent 1 death from lung cancer. RESULTS During follow-up, 1089 lung cancers were reported in the LDCT arm and 969 in the CXR arm of the NLST. The probability is 18.5% (95% CI, 5.4%-30.6%) that any lung cancer detected by screening with LDCT was an overdiagnosis, 22.5% (95% CI, 9.7%-34.3%) that a non-small cell lung cancer detected by LDCT was an overdiagnosis, and 78.9% (95% CI, 62.2%-93.5%) that a bronchioalveolar lung cancer detected by LDCT was an overdiagnosis. The number of cases of overdiagnosis found among the 320 participants who would need to be screened in the NLST to prevent 1 death from lung cancer was 1.38. CONCLUSIONS AND RELEVANCE More than 18% of all lung cancers detected by LDCT in the NLST seem to be indolent, and overdiagnosis should be considered when describing the risks of LDCT screening for lung cancer.

Selection Criteria for Lung-Cancer Screening

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 (PLCO(M2012)) 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 PLCO(M2012) criteria. We compared the accuracy of PLCO(M2012) 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, PLCO(M2012) 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 PLCO(M2012) risk (P=0.61 for interaction). CONCLUSIONS The use of the PLCO(M2012) model was more sensitive than the NLST criteria for lung-cancer detection.

Targeting of Low-Dose CT Screening According to the Risk of Lung-Cancer Death

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.).

Interstitial Lung Abnormalities in a CT Lung Cancer Screening Population: Prevalence and Progression Rate

PURPOSE To determine the prevalence of interstitial lung abnormalities (ILAs) at initial computed tomography (CT) examination and the rate of progression of ILAs on 2-year follow-up CT images in a National Lung Screening Trial population studied at a single site. MATERIALS AND METHODS The study was approved by the institutional review board and informed consent was obtained from all participants. Image review for this study was HIPAA compliant. We reviewed the CT images of 884 cigarette smokers who underwent low-dose CT at a single site in the National Lung Screening Trial. CT findings were categorized as having no evidence of ILA, equivocal for ILA, or ILA. We categorized the type of ILA as nonfibrotic (ground-glass opacity, consolidation, mosaic attenuation), or fibrotic (ground glass with reticular pattern, reticular pattern, honeycombing). We evaluated the temporal change of the CT findings (no change, improvement, or progression) of ILA at 2-year follow-up. A χ(2) with Fisher exact test or unpaired t test was used to determine whether smoking parameters were associated with progression of ILA at 2-year follow-up CT. RESULTS The prevalence of ILA was 9.7% (86 of 884 participants; 95% confidence interval: 7.9%, 11.9%), with a further 11.5% (102 of 884 participants) who had findings equivocal for ILA. The pattern was fibrotic in 19 (2.1%), nonfibrotic in 52 (5.9%), and mixed fibrotic and nonfibrotic in 15 (1.7%) of the 86 participants with ILA. The percentage of current smokers (P = .001) and mean number of cigarette pack-years (P = .001) were significantly higher in those with ILA than those without. At 2-year follow-up of those with ILA (n = 79), findings of nonfibrotic ILA improved in 49% of cases and progressed in 11%. Fibrotic ILA improved in 0% and progressed in 37% of cases. CONCLUSION ILA is common in cigarette smokers. Nonfibrotic ILA improved in about 50% of cases, and fibrotic ILA progressed in about 37%.

Identification of 14-3-3θ as an antigen that induces a humoral response in lung cancer

We have implemented a strategy to identify tumor antigens that induce a humoral immune response in lung cancer based on the analysis of tumor cell proteins. Chromatographically fractionated protein extracts from three lung cancer cell lines were subjected to Western blotting and hybridization with individual sera to determine serum antibody binding. Two sets of sera were initially investigated. One set consisted of sera from 19 newly diagnosed subjects with lung adenocarcinoma and 19 matched controls. A second independent set consisted of sera from 26 newly diagnosed subjects with lung adenocarcinoma and 24 controls matched for age, gender, and smoking history. One protein that exhibited significant reactivity with both sets of cancer sera ( P = 0.0008) was confidently identified by mass spectrometry as 14-3-3𝛉. Remarkably, significant autoantibody reactivity against 14-3-3𝛉 was also observed in an analysis of a third set consisting of 18 prediagnostic lung cancer sera collected as part of the Beta-Carotene and Retinol Efficacy Trial cohort study, relative to 19 matched controls ( P = 0.0042). A receiver operating characteristic curve constructed with a panel of three proteins consisting of 14-3-3𝛉 identified in this study, plus annexin 1 and protein gene product 9.5 proteins previously identified as associated with autoantibodies in lung cancer, gave a sensitivity of 55% at 95% specificity (area under the curve, 0.838) in discriminating lung cancer at the preclinical stage from matched controls. [Cancer Res 2007;67(24):12000–6]

Long-term Prognostic Role of Functional Limitations Among Women With Breast Cancer

BACKGROUND The long-term prognostic role of functional limitations among women with breast cancer is poorly understood. METHODS We studied a cohort of 2202 women with breast cancer at two sites in the United States, who provided complete information on body functions involving endurance, strength, muscular range of motion, and small muscle dexterity following initial adjuvant treatment. Associations of baseline functional limitations with survival were evaluated in delayed entry Cox proportional hazards models, with adjustment for baseline sociodemographic factors, body mass index, smoking, physical activity, comorbidity, tumor characteristics, and treatment. Difference in covariates between women with and without limitations was assessed with Pearson χ(2) and Student t tests. All statistical tests were two-sided. RESULTS During the median follow-up of 9 years, 112 deaths were attributable to competing causes (5% of the cohort) and 157 were attributable to breast cancer causes (7% of the cohort). At least one functional limitation was present in 39% of study participants. Proportionately, more breast cancer patients with functional limitations after initial adjuvant treatment were older, less educated, and obese (P < .001). In multivariable models, functional limitations were associated with a statistically significantly increased risk of death from all causes (hazard ratio [HR] = 1.40, 95% confidence interval [CI] = 1.03 to 1.92) and from competing causes (HR = 2.60, 95% CI = 1.69 to 3.98) but not from breast cancer (HR = 0.90, 95% CI = 0.64 to 1.26). The relationship between functional limitations and overall survival differed by tumor stage (among women with stage I and stage III breast cancer, HR = 2.02, 95% CI = 1.23 to 3.32 and HR = 0.74, 95% CI = 0.42 to 1.30, respectively). CONCLUSION In this prospective cohort study, functional limitations following initial breast cancer treatment were associated with an important reduction in all-cause and competing-cause survival, irrespective of clinical, lifestyle, and sociodemographic factors.

impact of lung cancer Screening results on Smoking cessation

BACKGROUND Lung cancer screening programs may provide opportunities to reduce smoking rates among participants. This study evaluates the impact of lung cancer screening results on smoking cessation. METHODS Data from Lung Screening Study participants in the National Lung Screening Trial (NLST; 2002-2009) were used to prepare multivariable longitudinal regression models predicting annual smoking cessation in those who were current smokers at study entry (n = 15489, excluding those developing lung cancer in follow-up). The associations of lung cancer screening results on smoking cessation over the trial period were analyzed. All hypothesis testing used two sided P values. RESULTS In adjusted analyses, smoking cessation was strongly associated with the amount of abnormality observed in the previous years screening (P < .0001). Compared with those with a normal screen, individuals were less likely to be smokers if their previous years screen had a major abnormality that was not suspicious for lung cancer (odds ratio [OR] = 0.811; 95% confidence interval [CI] = 0.722 to 0.912; P < .001), was suspicious for lung cancer but stable from previous screens (OR = 0.785; 95% CI = 0.706 to 0.872; P < .001), or was suspicious for lung cancer and was new or changed from the previous screen (OR = 0.663; 95% CI = 0.607 to 0.724; P < .001). Differences in smoking prevalence were present up to 5 years after the last screen. CONCLUSIONS Smoking cessation is statistically significantly associated with screen-detected abnormality. Integration of effective smoking cessation programs within screening programs should lead to further reduction in smoking-related morbidity and mortality.

Soluble Mesothelin-Related Peptide and Osteopontin As Markers of Response in Malignant Mesothelioma

PURPOSE In malignant mesothelioma (MM), radiologic assessment of disease status is difficult. Both soluble mesothelin-related peptide (SMRP) and osteopontin (OP) have utility in distinguishing MM from benign pleural disease. We evaluated whether SMRP and OP also correlated with the disease course of MM. PATIENTS AND METHODS Serial plasma samples from patients with MM were prospectively collected, and SMRP and OP levels were measured. Radiologic tests across time periods showing disease progression, stability, or shrinkage were compared with corresponding changes in SMRP/OP levels. RESULTS From 41 patients, 165 samples were collected (range, 2 to 10; median 4). At study entry, 37 of 41 patients had measurable disease, of whom 92% (34 of 37) had elevated baseline SMRP levels; four of 41 patients had no evidence of recurrence and each had normal baseline SMRP levels. In 21 patients receiving systemic therapy, percentage change in SMRP more than 10% correlated with the radiologic assessment by a trained thoracic radiologist (P < .001), by formal Response Evaluation Criteria in Solid Tumors (RECIST; P = .008), or by modified RECIST (P < .001). All seven patients who underwent surgical resection with negative margins had elevated preoperative SMRP levels that fell to normal postoperatively. Rising SMRP was observed in all patients with radiologic disease progression. No associations were found with OP. CONCLUSION Percentage changes in SMRP levels, but not changes in OP levels, are a potentially useful marker of disease course. These findings should be validated prospectively for a role as an objective adjunctive measure of disease course in both clinical trials and clinical practice.

The Utility of Nodule Volume in the Context of Malignancy Prediction for Small Pulmonary Nodules

BACKGROUND An estimated 150,000 pulmonary nodules are identified each year, and the number is likely to increase given the results of the National Lung Screening Trial. Decision tools are needed to help with the management of such pulmonary nodules. We examined whether adding any of three novel functions of nodule volume improves the accuracy of an existing malignancy prediction model of CT scan-detected nodules. METHODS Swensens 1997 prediction model was used to estimate the probability of malignancy in CT scan-detected nodules identified from a sample of 221 patients at the Medical University of South Carolina between 2006 and 2010. Three multivariate logistic models that included a novel function of nodule volume were used to investigate the added predictive value. Several measures were used to evaluate model classification performance. RESULTS With use of a 0.5 cutoff associated with predicted probability, the Swensen model correctly classified 67% of nodules. The three novel models suggested that the addition of nodule volume enhances the ability to correctly predict malignancy; 83%, 88%, and 88% of subjects were correctly classified as having malignant or benign nodules, with significant net improved reclassification for each (P<.0001). All three models also performed well based on Nagelkerke R2, discrimination slope, area under the receiver operating characteristic curve, and Hosmer-Lemeshow calibration test. CONCLUSIONS The findings demonstrate that the addition of nodule volume to existing malignancy prediction models increases the proportion of nodules correctly classified. This enhanced tool will help clinicians to risk stratify pulmonary nodules more effectively.