Dataset Information

Characteristics and Outcomes of Small Cell Lung Cancer Detected by CT Screening.

ABSTRACT:

Background

Previous studies with a limited number of patients have reported divergent findings on whether screening can detect small cell lung cancer (SCLC) at an earlier stage and whether there might be a survival benefit.

Methods

This study examined the characteristics of SCLC detected by using low-dose CT (LDCT) screening in the National Lung Screening Trial, a randomized study of individuals at high risk for developing lung cancer comparing LDCT imaging vs chest radiography. SCLC was denoted as screen detected if diagnosed ? 1 year of a positive screen or after a longer period but with no time gap between diagnostic procedures of > 1 year; interval detected if diagnosed ? 1 year of a negative screen; and nonscreen detected if the subject did not receive any screens or otherwise as postscreening.

Results

A total of 143 cases of SCLC were diagnosed, including 49 (34.2%) screen detected, 15 (10.5%) interval detected, and 79 (55.2%) nonscreened/postscreening. Of the screening phase-diagnosed cases (ie, screen or interval detected), a higher proportion of SCLC cases compared with NSCLC cases were interval detected (23% vs 5%; P < .0001). A higher proportion of all SCLC cases compared with NSCLC cases were advanced stage (III/IV: 86% vs 36%; P < .0001). The unfavorable SCLC stage distribution extended across screen-detected (80% stage III/IV), interval-detected (86%), and nonscreened/postscreening (90%) cancers. Among screen-detected SCLC, only 63.3% had ? 1 noncalcified nodule in the cancer lobe compared with 85.4% of NSCLC cases (P < .0001). Even with very small LDCT screen-detected nodules, a high proportion of SCLC cases were late stage. There was no significant difference in survival between screen- and interval-detected or postscreening SCLC.

Conclusions

"Early detection" with the use of LDCT imaging had no impact on SCLC outcomes. A successful screening modality should ideally detect SCLC earlier than when it can be detected on LDCT scans.

SUBMITTER: Thomas A

PROVIDER: S-EPMC6335258 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Publications

Characteristics and Outcomes of Small Cell Lung Cancer Detected by CT Screening.

Thomas Anish A Pattanayak Puskar P Szabo Eva E Pinsky Paul P

Chest 20180803 6

<h4>Background</h4>Previous studies with a limited number of patients have reported divergent findings on whether screening can detect small cell lung cancer (SCLC) at an earlier stage and whether there might be a survival benefit.<h4>Methods</h4>This study examined the characteristics of SCLC detected by using low-dose CT (LDCT) screening in the National Lung Screening Trial, a randomized study of individuals at high risk for developing lung cancer comparing LDCT imaging vs chest radiography. S ...[more]

PMID: 30080997

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Project description:Lung cancer can be classified into two main categories: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), which are different in treatment strategy and survival probability. The lung CT images of SCLC and NSCLC are similar such that their subtle differences are hardly visually discernible by the human eye through conventional imaging evaluation. We hypothesize that SCLC/NSCLC differentiation could be achieved via computerized image feature analysis and classification in feature space, as termed a radiomic model. The purpose of this study was to use CT radiomics to differentiate SCLC from NSCLC adenocarcinoma. Patients with primary lung cancer, either SCLC or NSCLC adenocarcinoma, were retrospectively identified. The post-diagnosis pre-treatment lung CT images were used to segment the lung cancers. Radiomic features were extracted from histogram-based statistics, textural analysis of tumor images and their wavelet transforms. A minimal-redundancy-maximal-relevance method was used for feature selection. The predictive model was constructed with a multilayer artificial neural network. The performance of the SCLC/NSCLC adenocarcinoma classifier was evaluated by the area under the receiver operating characteristic curve (AUC). Our study cohort consisted of 69 primary lung cancer patients with SCLC (n = 35; age mean ± SD = 66.91± 9.75 years), and NSCLC adenocarcinoma (n = 34; age mean ± SD = 58.55 ± 11.94 years). The SCLC group had more male patients and smokers than the NSCLC group (P < 0.05). Our SCLC/NSCLC classifier achieved an overall performance of AUC of 0.93 (95% confidence interval = [0.85, 0.97]), sensitivity = 0.85, and specificity = 0.85). Adding clinical data such as smoking history could improve the performance slightly. The top ranking radiomic features were mostly textural features. Our results showed that CT radiomics could quantitatively represent tumor heterogeneity and therefore could be used to differentiate primary lung cancer subtypes with satisfying results. CT image processing with the wavelet transformation technique enhanced the radiomic features for SCLC/NSCLC classification. Our pilot study should motivate further investigation of radiomics as a non-invasive approach for early diagnosis and treatment of lung cancer.

Project description:Lung cancer screening identifies cancers with heterogeneous behaviors. Some lung cancers will be identified among patients who had prior negative CT screens and upon follow-up scans develop a de novo nodule that was determined to be cancerous. Other lung cancers will be identified among patients who had one or more prior stable positive scans that were not determined to be lung cancer (indeterminate pulmonary nodules), but in follow-up scans was diagnosed with an incidence lung cancer. Using data from the CT arm of the National Lung Screening Trial, this analysis investigated differences in patient characteristics and survival endpoints between prevalence-, interval-, and screen-detected lung cancers, characterized based on sequence of screening results. Lung cancers immediately following a positive baseline (T0), and prior to the T1 screen, formed the prevalence cohort. Interval cancers were diagnosed following a negative screen at any time point prior to the next screening round. Two cohorts of screen-detected lung cancers (SDLC) were identified that had a baseline positive screen that was that was not determined to be lung cancer (i.e., an indeterminate pulmonary nodule), but in follow-up scans was diagnosed with an incidence lung cancer 12 (SDLC1) or 24 (SDLC2) months later. Two other incidence cohorts had screen-detected lung cancers that had baseline negative screen and upon follow-up scans developed a de novo nodule determined to be cancerous at 12 (SDLC3) or 24 (SDLC4) months later. Differences in patient characteristics, progression-free survival (PFS), and overall survival (OS) were assessed. The lung cancer-specific death rate was higher for SDLC3/SDLC4 compared to SDLC1/SDLC2 lung cancers (136.6/1,000 person-years vs. 71.3/1,000 person-years, P < 0.001). Moreover, PFS and OS were significantly lower for SDLC3/SDLC4 compared to SDLC1/SDLC2 (P < 0.004; P < 0.002, respectively). The findings were consistent when stratified by stage and histology. Multivariable Cox proportional models revealed that the SDLC3/SDLC4 case groups were associated with significantly poorer PFS (HR = 1.89; 95% CI 1.31-2.74) and OS (HR = 1.80; 95% CI 1.21-2.67) compared to SDLC1/SDLC2 lung cancers (HR = 1.00). Lung cancer patients who develop a de novo nodule that determined to be cancerous (i.e., at least one negative CT screen prior to cancer diagnosis) had poorer survival outcomes compared to patients who had at least one positive screen prior to cancer diagnosis. As such, the observation that de novo screen-detected are associated with poorer survival could be attributed to faster growing, more aggressive cancers that arose from a lung environment previously lacking focal abnormalities.

Project description:BackgroundMajor 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.MethodsWe 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.ResultsIn 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.ConclusionsPredictive 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.).

Project description:BackgroundPrevious studies of psychological burden in low-dose CT (LDCT) lung cancer screening trials may lack generalisability due to participation bias and control arms having elevated distress.MethodsCurrent and former smokers (n=787, aged 60-75) within a real-world screening demonstration pilot completed measures of lung cancer worry at three time points (T0: appointment, T1: next day, T2: 3 months) and anxiety and depression at two time points (T0 and T2). A 'screening unaware' community sample (n=383) with the same age and smoking characteristics completed these measures once (T0). Mean scores were compared by sample type and LDCT result.ResultsCompared with the community sample (T0), mean scores were higher in the screening sample, and statistically significantly increased in adjusted analyses, for lung cancer worry at T0 and T2 (mean (M): 9.32; 95% CI 8.96 to 9.69 vs M: 11.34; 11.09 to 11.59 and M: 11.88; 11.49 to 12.27), for anxiety at T0 and T2 (M: 3.32; 2.94 to 3.70 vs M: 4.73; 4.42 to 5.04 and M: 5.78; 5.33 to 6.23) and depression at T2 (M: 3.85; 3.44 to 4.27 vs M: 4.15; 3.76 to 4.55). Scores were highest for those with indeterminate (eg, T2 anxiety M: 6.93; 5.65 to 8.21) and incidental findings (primary care follow-up M: 5.34; 4.67 to 6.02) and those ineligible for screening (M: 6.51; 5.25 to 7.77). Being female, younger, not in paid employment, not married/cohabiting with a partner and lower education predicted poorer psychological outcomes at T0, but not T2 after adjusting for baseline scores. Mean scores remained within 'normal' clinical ranges.ConclusionPsychological distress was raised among high-risk individuals undergoing LDCT screening in a real-world setting, but overall differences were unlikely to be clinically meaningful. It will be critical to monitor the psychological impact of services longitudinally across diverse settings, including subgroups vulnerable to clinically elevated distress.Trial registrationThe Lung Screen Uptake Trial was registered prospectively with the International Standard Registered Clinical/soCial sTudy (ISRCTN) (Number: ISRCTN21774741) on 23 September 2015 and the National Institutes of Health ClinicalTrials.gov database (NCT02558101) on 22 September 2015.

Dataset Information

Characteristics and Outcomes of Small Cell Lung Cancer Detected by CT Screening.

Background

Methods

Results

Conclusions

Publications

Characteristics and Outcomes of Small Cell Lung Cancer Detected by CT Screening.

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