Incidence and Prevalence Analysis of Non-Small-Cell and Small-Cell Lung Cancer Using Administrative Data.
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SUBMITTER: Ricotti A
PROVIDER: S-EPMC8431612 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Purpose Prospectively identifying who will benefit from adjuvant chemotherapy (ACT) would improve clinical decisions for individual non-small-cell lung cancer (NSCLC) patients. Most current molecular signatures for lung cancer are prognostic only and provide limited information with regard to the functional importance of the genes selected. In this study, we aim to develop and validate a functional gene set that predicts the clinical benefit of ACT in NSCLC. Experimental Design An 18-hub-gene prognosis signature was developed through a systems biology approach using a large NSCLC dataset from the Director’s Challenge Consortium. The prognostic value of this signature was tested in NSCLC patients from UT Lung SPORE cohort and additional five public datasets. The 18-hub-gene set was then integrated with genome-wide functional (RNAi) data and genetic aberration data to derive a 12-gene predictive signature for ACT benefit in NSCLC. Results We showed that the 18-hub-gene set can robustly predict the prognosis of patients with adenocarcinoma in all validation datasets across four microarray platforms. The refined 12-gene functional set was successfully validated in two independent datasets. The predicted benefit group showed significant improvement in survival after ACT (JBR.10 clinical trial data: hazard ratio=0.36, p=0.038; UT Lung SPORE data: hazard ratio=0.34, p=0.017), while the predicted non-benefit group showed no survival improvement. Conclusions This is the first study to integrate genetic aberration, genome-wide RNAi functional data, and mRNA expression data to identify a functional gene set that is predictive for ACT benefits. This 12-gene predictive signature has been validated in two independent NSCLC cohorts. Patients were eligible to enter the study if they underwent curative resection for NSCLC at MD Anderson Cancer Center between December 1996 and June 2007, and patients with radiation therapy were excluded from the study. All tissue samples were obtained by surgical resection from patients who had provided written informed consent. Tissues were stored at −140°C after being snap frozen in liquid nitrogen. Serial sectioning of each sample was used to histologically evaluate tumor and malignant cells content before RNA extraction. The primary tumor tissues from 176 patients were selected randomly from similar samples in the UT Lung SPORE tumor collection based on stringent, predefined quality control procedures before any data analysis, including the presence of ≥70% tumor tissue and ≥50% malignant cells in the frozen tissue used for RNA extraction. In this cohort, 133 patients are adenocarcinomas (ADCs) and 43 patients are squamous cell carcinomas (SCCs); 49 patients received ACT (mainly Carboplatin plus Taxanes) and 127 patients did not receive ACT.
| S-ECPF-GEOD-42127 | biostudies-other
Project description:ObjectiveThe objective of the study was to estimate the incidence and prevalence of rheumatoid arthritis (RA) in Alberta using administrative health data.MethodsWe identified RA cases in patients 16 years and older by applying a national case definition to linked administrative health data (ie, hospital discharge abstract records, physician claims, and health insurance registry records) using a unique personal identifier. Incidence and prevalence are reported for the 2015-2016 fiscal year and a trend analysis from 2011-2012 to 2015-2016. Incidence and prevalence estimates were standardized using the 2011 Canadian census population.ResultsIn 2015-2016, the overall crude incidence was 0.74 [95% confidence interval (CI): 0.71-0.77] per 1000 and crude prevalence was 1.08% (95% CI: 1.07-1.09). The women-to-men crude incidence and prevalence sex ratios were 2.04 and 2.19, respectively. People aged 65 to 79 years had the highest incidence of RA, and the highest prevalence was observed among those 80 years and older. From 2011-2012 to 2015-2016, the overall age-standardized incidence decreased [0.97 (95% CI: 0.94-1.01) to 0.79 (95% CI: 0.76-0.82) per 1000], whereas age-standardized prevalence remained constant [1.17 (95% CI: 1.15-1.18) to 1.18 (95% CI: 1.17-1.19)].ConclusionIn Alberta, there was a decreasing trend in RA incidence over the study period, whereas prevalence was stable. These estimates, combined with clinical data, will be used to measure system performance for quality improvement and to inform simulation modeling for planning the expected demand for health services for patients living with RA.
| S-EPMC7368140 | biostudies-literature
Project description:IntroductionThe incidence and prevalence of diabetes within a population are important public health metrics. Pharmaceutical administrative data may offer a resource that can contribute to quantifying these measures using the recorded signals derived from the drugs used to treat people with diabetes.ObjectiveTo estimate the longitudinal incidence and prevalence of drug treated (DT) diabetes in Australia utilising an Australian Pharmaceutical Benefits Scheme (PBS) dataset and compare estimates with community survey data for all diabetes reported in the Australian National Health Survey (NHS).MethodsPersons with DT diabetes were identified within the PBS dataset using assigned Anatomic Therapeutic Chemical codes for 'Drugs used in diabetes'. Prevalent persons with DT diabetes were determined by a single annual treatment, and incident cases from the earliest treatment with diabetes medications. Counts were aggregated by age group and utilised Australian national census data as a denominator to calculate diabetes disease frequencies for the period 2004-14. Comparison of PBS prevalence data was made with NHS surveys over equivalent years.ResultsThe age adjusted incidence of DT diabetes was 3.4/1000 in 2006 and increased to 3.8/1000 in 2011 and 5.1/1000 in 2014. Age adjusted prevalence of DT diabetes in Australia also rose from 26.7/1000 in 2006 to 32.1/1000 in 2011 and 42.1/1000 in 2014. DT diabetes prevalence estimates correlated with NHS estimates of self-reported diabetes prevalence across age groups and in 2014 was r = 0.987. However, PBS estimates of DT diabetes prevalence generally underestimated NHS values of self-reported diabetes in older age groups with mean percentage differences of -22% to -3%. In contrast, PBS data captured more younger persons with diabetes in comparison to NHS data. These differences were then used to adjust DT diabetes incidence rates to provide age specific estimates that could potentially reflect diabetes incidence estimates acquired by community survey.ConclusionsPBS data representing dispensed medications prescribed to persons with diabetes offers a perspective for the assessment of diabetes incidence and prevalence. PBS derived DT diabetes prevalence estimates correlate well with community survey estimates of self-reported diabetes, but underestimate NHS data in older age groups. Calibrated DT incidence estimates may potentially reflect community survey derived diabetes incidence estimates and may offer a method for longitudinal monitoring.
| S-EPMC8121372 | biostudies-literature
Project description:Non small cell lung cancer is the leading cause of cancer related mortality in the western world. RNA expression profiles have been demonstrated to be associated with a specific clinical course of the disease. We used microarray analysis to capture the whole transcriptome of a series of lung cancer cell lines to extract RNA profiles associated with specific genomic lesions Keywords: steady state Lung cancer cell lines were exponentially grown and harvested during this phase of exponential growth
| S-ECPF-GEOD-14925 | biostudies-other
Project description:BACKGROUND:The study was conducted to investigate the clinicopathological features and prevalence of ROS1 gene fusion in Chinese patients with non-small cell lung cancer (NSCLC). METHODS:The presence of ROS1 fusion was assessed by quantitative real-time PCR. Associations between ROS1 fusion and clinical characteristics were analyzed. RESULTS:In total, 6066 patients with pathologically confirmed NSCLC and ROS1 fusion test results were enrolled. The average age was 60.89?±?10.60?years and fusion was detected in 157 (2.59%) patients. Fusion frequency was significantly correlated with age, gender, smoking status (all P?<?0.001), pathology type (P?=?0.017), and lymph node metastasis stage (P?=?0.027). ROS1 fusion-positive patients were significantly younger (55.68?±?11.34?vs. negative 61.02?±?10.44?years; P <?0.01). Fusion frequency was higher in women (3.71% vs. men 1.81%), never-smokers (3.33% vs. smokers 1.21%), and patients with adenocarcinoma (2.77% vs. squamous lung cancer 0.93%) and at advanced node stages (1.31%, 1.40%, 2.07%, and 3.23% for N0, N1, N2, and N3, respectively). No significant correlation between ROS1 fusion status and pathological stage was found in subgroups classified by pathological, tumor, or metastasis stage (P?>?0.05). Age, smoking status, and lymph node stage were statistically significantly correlated with ROS1 fusion frequency (all P?<?0.05); gender and pathology type were not significantly correlated with ROS1 fusion status after adjusting for smoking status. CONCLUSION:An overall ROS1 fusion frequency of 2.59% was confirmed in this study. ROS1 fusion was more prevalent among younger patients, never-smokers, and those at advanced node stages.
| S-EPMC6312842 | biostudies-other
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.
| S-EPMC7188953 | biostudies-literature
Project description:Pneumonitis is a potentially life-threatening complication of anticancer therapy, and future treatment decisions may be informed by characterizing patients receiving therapies in the real-world setting. In this study, the incidence of treatment-associated pneumonitis (TAP) was compared among patients with advanced non-small cell lung cancer receiving immune checkpoint inhibitors (ICI) or chemotherapies in either of two settings: randomized clinical trials (RCT) or real world data (RWD)-based clinical practice. Pneumonitis cases were identified using International Classification of Diseases codes (for RWD), or the Medical Dictionary for Regulatory Activities preferred terms (for RCTs). TAP was defined as pneumonitis diagnosed during treatment or within 30 days of the last treatment administration. Overall TAP rates in the RWD cohort were lower [ICI: 1.9%; 95% confidence interval (CI), 1.2-3.2; chemotherapy: 0.8%; 95% CI, 0.4-1.6] than overall rates in the RCT cohort (ICI: 5.6%; 95% CI, 5.0-6.2; chemotherapy: 1.2%; 95% CI, 0.9-1.5). Overall RWD TAP rates were similar to grade 3+ RCT TAP rates (ICI: 2.0%; 95% CI, 1.6-2.3; chemotherapy: 0.6%; 95% CI, 0.4-0.9). In both cohorts, higher TAP incidence was observed among patients with a past medical history of pneumonitis than those without, regardless of treatment group. On the basis of this sizable study leveraging RWD, TAP incidence was low in the RWD cohort, likely in part due to methodology used for RWD focusing on clinically significant cases. Past medical history of pneumonitis was associated with TAP in both cohorts.SignificancePneumonitis is a potentially life-threatening complication of anticancer treatment. As treatment options expand, management decisions become increasingly complex, and there is a greater need to understand the safety profiles of the treatment options in the real-world setting. Real-world data serve as an additional source of valuable information to complement clinical trial data and inform understanding of toxicity in patients with non-small cell lung cancer receiving ICIs or chemotherapies.
| S-EPMC9973394 | biostudies-literature
Project description:BACKGROUND:Certain cancer case ascertainment methods used in Quebec and elsewhere are known to underestimate the burden of cancer, particularly for some subgroups. Algorithms using claims data are a low-cost option to improve the quality of cancer surveillance, but have not frequently been implemented at the population-level. Our objectives were to 1) develop a colorectal cancer (CRC) case ascertainment algorithm using population-level hospitalization and physician billing data, 2) validate the algorithm, and 3) describe the characteristics of cases. METHODS:We linked physician billing, hospitalization, and tumor registry data for 2,013,430 Montreal residents age 20+ (2000-2010). We compared the performance of three algorithms based on diagnosis and treatment codes from different data sources. We described identified cases according to age, sex, socioeconomic status, treatment patterns, site distribution, and time trends. All statistical tests were two-sided. RESULTS:Our algorithm based on diagnosis and treatment codes identified 11,476 of the 12,933 incident CRC cases contained in the tumor registry as well as 2317 newly-captured cases. Our cases share similar overall time trends and site distributions to existing data, which increases our confidence in the algorithm. Our algorithm captured proportionally 35% more individuals age 50 and younger among CRC cases: 8.2% vs. 5.3%. The newly captured cases were also more likely to be living in socioeconomically advantaged areas. CONCLUSIONS:Our algorithm provides a more complete picture of population-wide CRC incidence than existing case ascertainment methods. It could be used to estimate long-term incidence trends, aid in timely surveillance, and to inform interventions, in both Quebec and other jurisdictions.
| S-EPMC5941340 | biostudies-literature
Project description:Snail is a zinc-finger transcription factor best known for its ability to down-regulate E-cadherin. Its established significance in embryology and organogenesis has been expanded to include a role in the tumor progression of a number of human cancers. In addition to E-cadherin, it has more recently been associated with the down-regulation and up-regulation of a number of other genes that affect important malignant phenotypes. After establishing the presence of up-regulated Snail in human non-small cell lung cancer specimens, we used microarrays to detail the global programme of gene expression in non-small cell lung cancer cell lines stably transduced to over-express Snail as compared to vector control cell lines. Non-small cell lung cancer cell lines (H441, H292, H1437) were stably transduced with a retroviral vector to over-express Snail. Elevated Snail and a corresponding down-regulation of E-cadherin was verified in the Snail over-expressing cell lines as compared to vector control cell lines by Western analysis. RNA extraction was performed and samples submitted to the UCLA Clinical Microarray Core for hybridization to Affymetrix arrays.
| S-ECPF-GEOD-16194 | biostudies-other
Project description:The impact of incomplete lung cancer resection on survival has never been systematically quantified, nor has the value of postoperative adjuvant therapy in this setting been determined.We evaluated lung cancer resections in the National Cancer Data Base from 2004 to 2011 to identify factors associated with margin involvement. We compared the survival of patients with and without positive margins and evaluated the impact of postoperative adjuvant therapy.Of 112,998 resections performed during the 8 years, 5,335 (4.7%) had positive margins. Patient demographic and clinical factors associated with an increased adjusted OR of incomplete resection included black race (p = 0.006), age-based Medicare insurance (p = 0.006), urban residence (p = 0.01), histologic diagnosis of squamous cell carcinoma, high tumor grade, tumor overlapping more than one lobe, and advanced pathologic stage (p < 0.001 for all clinical factors). Community cancer programs (p = 0.002), institutions with high proportions of underinsured patients (p = 0.01), and institutions with a lower volume of cancer resections (p = 0.006) also had an increased adjusted OR. The crude 5-year survival rates of patients with complete versus incomplete resections were 58.5% versus 33.8% (log-rank p < 0.001). After an incomplete resection, adjuvant chemotherapy was associated with improved 5-year survival across all stages (p < 0.01); radiotherapy was associated with worse survival in patients with stage I disease (p < 0.001).Margin involvement significantly impaired survival after lung cancer resection irrespective of stage. Causative institutional and provider practices should be identified to minimize this adverse outcome. Postoperative adjuvant chemotherapy mitigated mortality risk independently of stage, whereas postoperative radiotherapy exacerbated the risk in patients with stage I disease. These findings need validation in prospective trials.
| S-EPMC4714753 | biostudies-literature