Prostate, Lung, Colorectal And Ovarian Research Articles

Lead-Time Trajectory of CA19-9 as an Anchor Marker for Pancreatic Cancer Early Detection

There is substantial interest in liquid biopsy approaches for cancer early detection among subjects at risk, using multi-marker panels. CA19-9 is an established circulating biomarker for pancreatic cancer; however, its relevance for pancreatic cancer early detection or for monitoring subjects at risk has not been established. CA19-9 levels were assessed in blinded sera from 175 subjects collected up to 5 years before diagnosis of pancreatic cancer and from 875 matched controls from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. For comparison of performance, CA19-9 was assayed in blinded independent sets of samples collected at diagnosis from 129 subjects with resectable pancreatic cancer and 275 controls (100 healthy subjects; 50 with chronic pancreatitis; and 125 with noncancerous pancreatic cysts). The complementary value of 2 additional protein markers, TIMP1 and LRG1, was determined. In the PLCO cohort, levels of CA19-9 increased exponentially starting at 2 years before diagnosis with sensitivities reaching 60% at 99% specificity within 0 to 6 months before diagnosis for all cases and 50% at 99% specificity for cases diagnosed with early-stage disease. Performance was comparable for distinguishing newly diagnosed cases with resectable pancreatic cancer from healthy controls (64% sensitivity at 99% specificity). Comparison of resectable pancreatic cancer cases to subjects with chronic pancreatitis yielded 46% sensitivity at 99% specificity and for subjects with noncancerous cysts, 30% sensitivity at 99% specificity. For prediagnostic cases below cutoff value for CA19-9, the combination with LRG1 and TIMP1 yielded an increment of 13.2% in sensitivity at 99% specificity (P= .031) in identifying cases diagnosed within 1 year of blood collection. CA19-9 can serve as an anchor marker for pancreatic cancer early detection applications.

Association study between genetic variants in retinol metabolism pathway genes and prostate cancer risk

BackgroundEvidence suggests that serum retinol level is associated with prostate cancer risk, but the association between genetic variants in the retinol metabolism pathway genes and prostate cancer risk remains unclarified.MethodsSingle‐nucleotide polymorphisms (SNPs) in 31 genes in the retinol metabolism pathway were genotyped to evaluate the association with prostate cancer risk in 4,662 cases and 3,114 controls from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. The gene expression analysis was evaluated using data from the Gene Expression Omnibus (GEO) datasets and the Cancer Genome Atlas (TCGA) database. Data from the Genotype‐Tissue Expression (GTEx) project dataset were utilized to perform the expression quantitative trait loci (eQTL) analysis.ResultsTwo SNPs were significantly associated with prostate cancer risk [rs1330286 in ALDH1A1: odds ratio (OR) = 0.88, 95% confidence interval (CI) = 0.83‐0.94, p = 2.45 × 10−4; rs4646653 in ALDH1A3: OR = 1.17, 95% CI =1.07‐1.27, p = 4.33 × 10−4]. Moreover, the mRNA level of ALDH1A3 was significantly higher in prostate cancer tissues than in normal tissues in both TCGA datasets and GEO datasets (p = 1.63 × 10−12 and p = 4.33 × 10−2, respectively). rs1330286 was an eQTL of ALDH1A1 (P = 2.90 × 10−3).ConclusionOur findings highlight that genetic variants in retinol metabolism pathway genes are associated with prostate cancer risk.

Deep hiearchical multi-label classification applied to chest X-ray abnormality taxonomies.

Chest X-rays (CXRs) are a crucial and extraordinarily common diagnostic tool, leading to heavy research for computer-aided diagnosis (CAD) solutions. However, both high classification accuracy and meaningful model predictions that respect and incorporate clinical taxonomies are crucial for CAD usability. To this end, we present a deep hierarchical multi-label classification (HMLC) approach for CXR CAD. Different than other hierarchical systems, we show that first training the network to model conditional probability directly and then refining it with unconditional probabilities is key in boosting performance. In addition, we also formulate a numerically stable cross-entropy loss function for unconditional probabilities that provides concrete performance improvements. Finally, we demonstrate that HMLC can be an effective means to manage missing or incomplete labels. To the best of our knowledge, we are the first to apply HMLC to medical imaging CAD. We extensively evaluate our approach on detecting abnormality labels from the CXR arm of the Prostate, Lung, Colorectal and Ovarian (PLCO) dataset, which comprises over 198,000 manually annotated CXRs. When using complete labels, we report a mean area under the curve (AUC) of 0.887, the highest yet reported for this dataset. These results are supported by ancillary experiments on the PadChest dataset, where we also report significant improvements, 1.2% and 4.1% in AUC and average precision, respectively over strong "flat" classifiers. Finally, we demonstrate that our HMLC approach can much better handle incompletely labelled data. These performance improvements, combined with the inherent usefulness of taxonomic predictions, indicate that our approach represents a useful step forward for CXR CAD.

Deep Learning Using Chest Radiographs to Identify High-Risk Smokers for Lung Cancer Screening Computed Tomography: Development and Validation of a Prediction Model.

Lung cancer screening with chest computed tomography (CT) reduces lung cancer death. Centers for Medicare & Medicaid Services (CMS) eligibility criteria for lung cancer screening with CT require detailed smoking information and miss many incident lung cancers. An automated deep-learning approach based on chest radiograph images may identify more smokers at high risk for lung cancer who could benefit from screening with CT. To develop and validate a convolutional neural network (CXR-LC) that predicts long-term incident lung cancer using data commonly available in the electronic medical record (EMR) (chest radiograph, age, sex, and whether currently smoking). Risk prediction study. U.S. lung cancer screening trials. The CXR-LC model was developed in the PLCO (Prostate, Lung, Colorectal, and Ovarian) Cancer Screening Trial (n = 41856). The final CXR-LC model was validated in additional PLCO smokers (n = 5615, 12-year follow-up) and NLST (National Lung Screening Trial) heavy smokers (n = 5493, 6-year follow-up). Results are reported for validation data sets only. Up to 12-year lung cancer incidence predicted by CXR-LC. The CXR-LC model had better discrimination (area under the receiver-operating characteristic curve [AUC]) for incident lung cancer than CMS eligibility (PLCO AUC, 0.755 vs. 0.634; P < 0.001). The CXR-LC model's performance was similar to that of PLCOM2012, a state-of-the-art risk score with 11 inputs, in both the PLCO data set (CXR-LC AUC of 0.755 vs. PLCOM2012 AUC of 0.751) and the NLST data set (0.659 vs. 0.650). When compared in equal-sized screening populations, CXR-LC was more sensitive than CMS eligibility in the PLCO data set (74.9% vs. 63.8%; P = 0.012) and missed 30.7% fewer incident lung cancers. On decision curve analysis, CXR-LC had higher net benefit than CMS eligibility and similar benefit to PLCOM2012. Validation in lung cancer screening trials and not a clinical setting. The CXR-LC model identified smokers at high risk for incident lung cancer, beyond CMS eligibility and using information commonly available in the EMR. None.

Reproductive and hormonal factors and bladder cancer risk: a prospective study and meta-analysis.

Bladder cancer is three to four times more common among men than women. The objectives of this study were to explore the association between reproductive and hormonal factors and risk of bladder cancer among women using data from the Prostate, Lung, Colorectal and Ovarian (PLCO) cohort, and to perform a meta-analysis based on cohort studies. After a median of 11.6 years of follow-up, 237 incident bladder cancer cases were identified in PLCO cohort. Compared with menopause at 50-54 years, earlier menopause (< 45 years) was positively but not significantly associated with bladder cancer risk (HR 1.25, 95% CI 0.91-1.71; p = 0.176). In the meta-analysis, parous women had significantly lower bladder cancer risk than nulliparous women (pooled HR 0.79, 95% CI 0.73-0.86). In addition, menopause at an earlier age was significantly associated with a higher risk of bladder cancer (pooled HR 1.22, 95% CI 1.06-1.40). In conclusion, this study indicated a greater risk in bladder cancer among nulliparous women and among women with early menopause. Further studies are needed to understand the underlying mechanisms.

Relationship between prediagnostic body mass index trajectory and colorectal adenomas: an analysis of the PLCO cancer screening trial.

BackgroundStudies on the relationship between lifetime body mass index (BMI) trajectory and colorectal premalignant precursor lesions are limited. This study aimed to assess the relationship between prediagnostic adulthood BMI trajectory and the risk of colorectal adenomas using data from the Prostate, Lung, Colorectal and Ovarian (PLCO) cancer screening trial.MethodsIn total, 39,824 participants in the intervention arm of the prospective PLCO cohort, who have undergone at least one colonoscopy or sigmoidoscopy examination with a confirmed diagnosis of colorectal adenomas, were enrolled and divided into four groups (underweight, normal weight, overweight, and obese) according to BMI during each age period. SAS Proc Traj was used to establish the BMI trajectory model. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs).ResultsCompared with normal weight, overweight or obesity significantly increased colorectal adenomas risk in each age period after 30 years. Specifically, obesity in the 50s was most closely related to colorectal adenomas risk [HR: 1.32, 95% CI: (1.22, 1.43)]. BMI gain from the age of 40 to 50 [HR: 1.25, 95% CI: (1.11, 1.42)] showed the strongest correlation with an increased incidence of colorectal adenomas, followed by that from the age of 30 to 50 [HR: 1.19, 95% CI: (1.10, 1.29)], the age of 20 to 50 [HR: 1.16, 95% CI: (1.10, 1.24)], the age of 20 to 40 [HR: 1.14, 95% CI: (1.05, 1.23)], and the age of 20 to 30 [HR: 1.13, 95% CI: (1.02, 1.26)]. Additionally, compared with those who maintained normal weight throughout adulthood, those who progressed from normal weight to obesity [HR: 1.15, 95% CI: (1.06, 1.25)], or from overweight to obesity [HR: 1.33, 95% CI: (1.11, 1.61)], had a higher risk of colorectal adenomas.ConclusionsOverweight and obesity increased the risk of colorectal adenomas, and this risk increased with advancing age.

Novel genetic variants in genes of the Fc gamma receptor-mediated phagocytosis pathway predict non-small cell lung cancer survival.

BackgroundBoth antibody-dependent cellular cytotoxicity and phagocytosis activate innate immunity, and the Fc gamma receptor (FCGR)-mediated phagocytosis is an integral part of the process. We assessed associations between single-nucleotide polymorphisms (SNPs) in FCGR-related genes and survival of patients with non-small cell lung cancer (NSCLC).MethodsWe evaluated associations between 24,734 (SNPs) in 97 FCGR-related genes and survival of 1,185 patients with NSCLC using a published genome-wide association study (GWAS) dataset from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial and validated the results in another independent dataset of 894 NSCLC patients.ResultsIn the single-locus analysis with Bayesian false discovery probability (BFDP) for multiple testing correction, we found 1,084 SNPs to be significantly associated overall survival (OS) (P<0.050 and BFDP ≤0.80), of which two independent SNPs (PLCG2 rs9673682 T>G and PLPP1 rs115613985 T>A) were further validated in another GWAS dataset of 894 patients from the Harvard Lung Cancer Susceptibility (HLCS) Study, with combined allelic hazards ratios for OS of 0.87 [95% confidence interval (CI): 0.81–0.94 and P=5.90×10−4] and 1.18 (95% CI: 1.08–1.29 and 1.32×10−4, respectively). Expression quantitative trait loci analysis showed that the rs9673682 G allele was significantly correlated with increased mRNA expression levels of PLCG2 in 373 transformed lymphoblastoid cell-lines (P=7.20×10−5). Additional evidence from differential expression analysis further supported a tumor-suppressive effect of PLCG2 on OS of patients with lung cancer, with lower mRNA expression levels in both lung squamous carcinoma and adenocarcinoma than in adjacent normal tissues.ConclusionsGenetic variants in PLCG2 of the FCGR-mediated phagocytosis pathway may be promising predictors of NSCLC survival, possibly through modulating gene expression, but additional investigation of the molecular mechanisms of PLPP1 rs115613985 is warranted.

Causal Proportional Hazards Estimation with a Binary Instrumental Variable.

Instrumental variables (IV) are a useful tool for estimating causal effects in the presence of unmeasured confounding. IV methods are well developed for uncensored outcomes, particularly for structural linear equation models, where simple two-stage estimation schemes are available. The extension of these methods to survival settings is challenging, partly because of the nonlinearity of the popular survival regression models and partly because of the complications associated with right censoring or other survival features. Motivated by the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer screening trial, we develop a simple causal hazard ratio estimator in a proportional hazards model with right censored data. The method exploits a special characterization of IV which enables the use of an intuitive inverse weighting scheme that is generally applicable to more complex survival settings with left truncation, competing risks, or recurrent events. We rigorously establish the asymptotic properties of the estimators, and provide plug-in variance estimators. The proposed method can be implemented in standard software, and is evaluated through extensive simulation studies. We apply the proposed IV method to a data set from the Prostate, Lung, Colorectal and Ovarian cancer screening trial to delineate the causal effect of flexible sigmoidoscopy screening on colorectal cancer survival which may be confounded by informative noncompliance with the assigned screening regimen.

Other- and all-cause Mortality among women with breast cancer

BackgroundAdvances in early detection and treatment of breast cancer (BrCA) have led to better survival. Consequently, more women with BrCA now die from non-BrCA causes. We investigated all-cause and other-cause (non-BrCA) survival among women with BrCA. MethodsFrom the Prostate, Lung, Colorectal and Ovarian (PCLO) cohort, we selected women diagnosed with BrCA from 1994-2014. To compare survival of cases to non-cases, we used exposure density sampling. We computed standard mortality ratios (SMRs) and performed Cox proportional hazards models with matched case-control sets, controlling for demographics (Model I) and additional covariates (Model II). We also examined survival by stage within BrCA cases. ResultsAmong 78,215 women enrolled in PLCO, there were 1211 in-situ and 4790 invasive BrCA cases. 15-year survival rates were 97.1 % (BrCA-specific) and 77.2 % (other-cause) among in-situ and 86.4 % (BrCA-specific) and 73.4 % (other-cause) among invasive cases. For other-cause mortality, in-situ cases had lower risk in models I (HR = 0.74; 95 % CI:0.62-0.89) and II (HR = 0.75; 95 % CI:0.62-0.92) versus controls. All-cause mortality HRs for in-situ cases were 0.83 (95 % CI:0.70-0.99) and 0.85 (95 % CI:0.70–1.02) in Models I and II, respectively. Other-cause mortality was similar among invasive cases and controls. Within BrCA cases, higher stage was associated with increased other-cause mortality; HRs were 1.2 (95 % CI:1.1–1.5) and 1.7 (95 % CI:1.2–2.3) for stage II and III/IV versus stage I (Model II). DiscussionMortality from other causes exceeded that of BrCA in both in-situ and invasive cases, highlighting the importance of managing patients’ chronic conditions during and following cancer treatment.

Endogenous estradiol and inflammation biomarkers: potential interacting mechanisms of obesity-related disease.

Disentangling the effects of endogenous estrogens and inflammation on obesity-related diseases requires a clearer understanding of how the two biological mechanisms relate to each other. We studied 155 healthy postmenopausal women not taking menopausal hormone therapy enrolled in the Prostate Lung Colorectal and Ovarian (PLCO) screening cancer trial. From a baseline blood draw, we measured endogenous estradiol and 69 inflammation biomarkers: cytokines, chemokines, adipokines, angiogenic factors, growth factors, acute phase proteins, and soluble receptors. We evaluated the estradiol-inflammation relationship by assessing associations across different models (linear, ordinal logistic, and binary logistic) using a variety of estradiol classifications. We additionally investigated the estradiol-inflammation relationship stratified by baseline obesity status (BMI < 30 stratum and BMI > 30 stratum). Associations of estradiol with 7 inflammation biomarkers met p < 0.05 statistical significance in linear and ordinal models: C-reactive protein (CRP), adiponectin, chemokine (C-X-C motif) ligand-6, thymus activation-regulated chemokine, eosinophil chemotactic protein, plasminogen activator inhibitor-1, and serum amyloid A. The positive association between estradiol and CRP was robust to model changes. Each standard deviation increase in endogenous estradiol doubled a woman's odds of having CRP levels higher than the study median (odds ratio 2.29; 95% confidence interval 1.28, 4.09). Estradiol was consistently inversely associated with adiponectin. Other estradiol-inflammation biomarker associations were not robust to model changes. Endogenous estradiol appears to be associated with CRP and adiponectin; the evidence is limited for other inflammation biomarkers.

Contribution of Surveillance Colonoscopy to Colorectal Cancer Prevention

The contribution of surveillance colonoscopy, as opposed to that of initial colonoscopy examination, to prevention of colorectal cancer (CRC) is uncertain. We estimated the preventive effect of surveillance colonoscopy by applying the recently developed metric of adenoma dwell time avoided needed to prevent 1 CRC case (DTA). We followed subjects in the prostate, lung, colorectal and ovarian (PLCO) cancer screening trial who underwent colonoscopies following positive findings from sigmoidoscopies (colonoscopy cohort, n = 15,935) for CRC incidence for 10 years. The number and timing of adenomas removed during surveillance were measured in a subset (n = 3492) of patients and extrapolated to the entire cohort to estimate the total avoided adenoma dwell time. A previously determined DTA value of 612 dwell years was applied to estimate the number of CRC cases prevented by surveillance. Proportional reduction in CRC was computed as CP/(CO+CP), where CO and CP are observed and estimated prevented cases, respectively. In the colonoscopy cohort of the PLCO, 2882 subjects had advanced adenomas (AAs), 572 had 3 or more non-advanced adenomas (NAA3+), 4496 had 1-2 non-advanced adenomas (NAA1-2), and 7985 had no adenoma (NA). The mean number of subsequent colonoscopy examinations over 10 years were 1.80 for subjects with AAs, 1.63 for subjects with NAA3+, and 1.46 for subjects with NAA1-2. Average years of avoided adenoma dwell time per subject were 4.0 for subjects with AAs, 5.5 for subjects with NAA3+, and 2.4 for subjects with NAA1-2. There were 56 cases of CRC in subjects with AAs, 4 cases of CRC in subjects with NAA3+, and 33 cases of CRC in subjects with NAA1-2. Estimated proportional reductions in CRC incidence were 25.0% in subjects with AAs (95% CI, 16%-34%), 34.4% in subjects with NAA1-2 (95% CI, 25%-40%), and 30.4% overall (in subjects with AAs, NAA3+, or NAA1-2; 95% CI, 25%-40%). Absolute CRC incidence reductions were 7.1 per 10,000 PY in subjects with AAs and 4.1 per 10,000 PY in subjects with NAA1-2. Using the recently developed metric of DTA, we estimated that surveillance colonoscopy in the PLCO colonoscopy cohort during 10 years of follow up prevented 30% of CRC cases. Because the methodology for estimation is indirect, the true effect is uncertain.

Novel genetic variants in KIF16B and NEDD4L in the endosome-related genes are associated with nonsmall cell lung cancer survival.

The endosome is a membrane-bound organ inside most eukaryotic cells, playing an important role in adaptive immunity by delivering endocytosed antigens to both MHC class I and II pathways. Here, by analyzing genotyping data from two published genome-wide association studies (GWASs), we evaluated associations between genetic variants in the endosome-related gene-set and survival of patients with nonsmall cell lung cancer (NSCLC). The discovery included 44,112 (3,478 genotyped and 40,634 imputed) single-nucleotide polymorphisms (SNPs) in 220 genes in a singlelocus analysis for their associations with survival of 1,185 NSCLC patients from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. After validation of the 821 survival-associated significant SNPs in additional 984 NSCLC patients from the Harvard Lung Cancer Susceptibility Study, 14 SNPs remained significant. The final multivariate stepwise Cox proportional hazards regression modeling of the PLCO dataset identified three potentially functional and independent SNPs (i.e., KIF16B rs1555195 C>T, NEDD4L rs11660748 A>G and rs73440898 A>G) with an adjusted hazards ratio (HR) of 0.86 (95% confidence interval [CI] = 0.79-0.94, p = 0.0007), 1.31 (1.16-1.47, p = 6.0 × 10-5 ) and 1.27 (1.12-1.44, p = 0.0001) for overall survival (OS), respectively. Combined analysis of the adverse genotypes of these three SNPs revealed a trend in the genotype-survival association (ptrend < 0.0001 for OS and ptrend < 0.0001 for disease-specific survival). Furthermore, the survival-associated KIF16B rs1555195T allele was significantly associated with decreased mRNA expression levels of KIF16B in both lung tissues and blood cells. Therefore, genetic variants of the endosome-related genes may be biomarker for NSCLC survival, possibly through modulating the expression of corresponding genes.

Dietary fiber intake and the risk of bladder cancer in the Prostate, Lung, Colorectal and Ovarian (PLCO) cohort.

Dietary fiber intake has been implicated as a protective factor for several human cancers in multiple epidemiologic studies. However, little is known about the effect of fiber intake on bladder cancer. This study examines the association between dietary fiber intake and bladder cancer risk among participants in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. A total of 101 721 participants were included in this study as they completed both the baseline questionnaire and the diet history questionnaire (cancer free before completion of the diet history questionnaire). Hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs) were estimated using the Cox proportional hazards regression model. After a median of 12.5 years of follow-up, 776 new cases of bladder cancer were identified. Higher intake of total fiber, insoluble fiber and soluble fiber were not significantly associated with a reduced risk of bladder cancer. The multi-adjusted HRs (95 CIs) of highest versus lowest tertile of intake were 0.83 (0.66-1.04) for total fiber (P for trend = 0.098), 0.83 (95% CI: 0.67-1.03) for insoluble fiber (P for trend = 0.092) and 0.86 (95% CI: 0.68-1.08) for soluble fiber (P for trend = 0.168), respectively. There was no significant interaction of potential confounders, including education, body mass index and smoking status, with total fiber intake on bladder cancer risk. In summary, the findings of this prospective study show that there is no obvious evidence for a link between dietary fiber consumption and bladder cancer risk. Further large cohort studies are warranted to confirm these findings.

Fiber intake and the risk of head and neck cancer in the prostate, lung, colorectal and ovarian (PLCO) cohort.

Although the protective role of dietary fiber on cancer risk has been reported in several epidemiological studies, the association of fiber intake on head and neck cancer (HNC) risk is still unclear. We investigated the association between fiber intake and the risk of HNC using data from the Prostate, Lung, Colorectal and Ovarian (PLCO) cancer screening trial. Among 101,700 participants with complete dietary information, 186 participants developed HNC during follow-up (January 1998 to May 2011). Dietary data were collected using a self-administered food-frequency questionnaire (1998-2005). We estimated hazard ratios (HRs) and the corresponding 95% confidence intervals (CI), using the Cox proportional hazards model. Higher intake of total fiber, insoluble fiber and soluble fiber was associated with decreased HNC risks, with a significant trend. The HRs of highest vs. the lowest tertile of intake were 0.43 (95%CI: 0.25-0.76) for total fiber, 0.38 (95%CI: 0.22-0.65) for insoluble fiber, and 0.44 (95%CI: 0.25-0.79) for soluble fiber. These inverse association were consistent in oral cavity and pharyngeal cases, but the impact of fiber intake was weaker in laryngeal cases. We did not observe any significant interaction of potential confounders, including smoking and drinking, with total fiber intake on HNC risk. These findings support evidence of a protective role of dietary fiber on HNC risk.

Evaluation of Classification Models for Predicting Mortality Rate Using Thyroid Cancer Data

Machine Learning (ML) can potentially enhance predictions in real-life domains. This study presents an evaluation and comparison of different ML methods which can be applied on thyroid cancer dataset, called Prostate, Lung, Colorectal and Ovarian (PLCO), of approximately 155,000 participants with thyroid cancer occurrence and mortality incidence. The ML models are explored for predicting mortality rates of patients with thyroid cancer. These models include the Logistic Regression model (LR), K-Neighbors model (KN), Support Vector Classifier (SVC), Gaussian Naive Bayes (GNB), decision tree classifier (DT), Random Forest classifier (RF), ada boost classifier (AdaB) and Gradient Boosting classifier (GB). The results reveal that AdaB and GB classifiers have the best performance among the models. The results also show that different predictive models can significantly differ with others in terms of their performance evaluated by various metrics. This study shows that the chosen parameters for classifiers will affect their performance; therefore, it is important to explore and evaluate them before final implementation.

Association of Nonadherence to Cancer Screening Examinations With Mortality From Unrelated Causes

ImportancePatient nonadherence to chronic disease prevention guidelines is associated with increased mortality. Nonadherence to offered cancer screening tests may be associated with mortality among middle-aged and older adults.ObjectiveTo evaluate the association between nonadherence to cancer screening tests and mortality in the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening trial, excluding mortality from cancers studied in the trial.Design, Setting, and ParticipantsRandomization at 10 US screening centers occurred from November 8, 1993, to July 2, 2001. Original follow-up was through 13 years or December 31, 2009. Participants were re-consented to further follow-up starting May 18, 2011, and were observed until December 31, 2012. Protocol screening tests for the PLCO Cancer Screening trial intervention arm participants (N = 77 443) included chest radiographs and flexible sigmoidoscopy for both sexes, prostate-specific antigen tests and digital rectal examinations for men, and cancer antigen 125 tests and transvaginal ultrasonography for women. At baseline, participants completed a self-administered questionnaire. The cohort was classified into those receiving all sex-specified PLCO Cancer Screening trial screening tests at baseline (fully adherent), those receiving some but not all baseline tests (partially adherent), and those receiving no baseline tests (nonadherents). Secondary analysis was ad hoc in the original trial protocol. Statistical analysis was conducted from November 24, 2017, to August 29, 2018.Main Outcomes and MeasuresMortality was ascertained via mailed annual study update questionnaires and searches of the National Death Index. Cox proportional hazards regression was used to analyze the association between mortality and adherence, controlling for various covariates.ResultsOf 77 443 participants in the intervention arm, 64 567 (29 537 women and 35 030 men; mean [SD] age, 62.3 [5.3] years) were included in the analysis based on consenting to trial participation before randomization and being eligible for all screening tests. Overall, 55 065 participants (85.3%) were adherent, 2548 (3.9%) were partially adherent, and 6954 (10.8%) were nonadherent with the baseline screening protocol. Within 10 years of follow-up, the hazard ratio of mortality, excluding deaths from cancers studied in the PLCO Cancer Screening trial and controlling only for age, sex, and race/ethnicity (model 1), was 1.73 (95% CI, 1.60-1.89) for nonadherent compared with fully adherent participants and 1.36 (95% CI, 1.19-1.54) for partially compared with fully adherent participants. After adjustment for medical risk factors for mortality and behavioral-related factors (model 2), the hazard ratio decreased to 1.46 (95% CI, 1.34-1.59) for nonadherent compared with fully adherent participants.Conclusions and RelevanceAmong participants in a screening trial for multiple cancers, a nonadherence behavior profile marked by nonadherence to protocol screenings was associated with higher overall mortality (excluding deaths from cancers studied in the trial). The generalizability of this finding to routine clinical practice should be assessed.Trial RegistrationClinicalTrials.gov identifier: NCT00002540

Potentially functional genetic variants in the complement-related immunity gene-set are associated with non-small cell lung cancer survival.

The complement system plays an important role in the innate and adaptive immunity, complement components mediate tumor cytolysis of antibody-based immunotherapy, and complement activation in the tumor microenvironment may promote tumor progression or inhibition, depending on the mechanism of action. In the present study, we conducted a two-phase analysis of two independently published genome-wide association studies (GWASs) for associations between genetic variants in a complement-related immunity gene-set and overall survival of non-small cell lung cancer (NSCLC). The GWAS dataset from Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial was used as the discovery, and multivariate Cox proportional hazards regression with false-positive report probability for multiple test corrections were performed to evaluate associations between 14,699 single-nucleotide polymorphisms (SNPs) in 111 genes and survival of 1,185 NSCLC patients. The identified significant SNPs in a single-locus analysis were further validated with 984 NSCLC patients in the GWAS dataset from the Harvard Lung Cancer Susceptibility (HLCS) Study. The results showed that two independent, potentially functional SNPs in two genes (VWF rs73049469 and ITGB2 rs3788142) were significantly associated with NSCLC survival, with a combined hazards ratio (HR) of 1.22 [95% confidence interval (CI) = 1.07-1.40, P = 0.002] and 1.16 (1.07-1.27, 6.45 × 10-4 ), respectively. Finally, we performed expression quantitative trait loci (eQTL) analysis and found that survival-associated genotypes of VWF rs73049469 were also significantly associated with mRNA expression levels of the gene. These results indicated that genetic variants of the complement-related immunity genes might be predictors of NSCLC survival, particularly for the short-term survival, possibly by modulating the expression of genes involved in the host immunity.

Extended follow-up for prostate cancer incidence and mortality among participants in the Prostate, Lung, Colorectal and Ovarian randomized cancer screening trial.

To examine prostate cancer (PCa) incidence and mortality by arm in the randomized Prostate, Lung, Colorectal and Ovarian (PLCO) cancer screening trial. Patients aged 55-74 years at 10 screening centres were randomized between 1993 and 2001 to an intervention or usual care arm. Patients in the intervention arm received six annual prostate-specific antigen (PSA) tests and four annual digital rectal examinations. The patients were followed for PCa incidence and for mortality via active follow-up processes and by linkage to state cancer registries and the National Death Index. For cancers identified through active follow-up, trial abstractors recorded the mode of diagnosis (screen-detected, symptomatic, other). A total of 38 340 patients were randomized to the intervention arm and 38 343 to a usual care arm. The median follow-up for mortality was 16.9 (intervention) and 16.7 years (usual care). There were 333 (intervention) and 352 (usual care) PCa cancer deaths, giving rates (per 10 000 person-years) of 5.5 and 5.9, respectively, and a rate ratio (RR) of 0.93 (95% confidence interval [CI] 0.81-1.08; P = 0.38). The RR for overall PCa incidence was 1.05 (95% CI 1.01-1.09). The RRs by Gleason category were 1.17 (95% CI 1.11-1.23) for Gleason 2-6, 1.00 (95% CI 0.93-1.07) for Gleason 7 and 0.89 (95% CI 0.80-0.99) for Gleason 8-10 disease. By mode of detection, during the trial's screening phase, 13% of intervention arm vs 27% of usual care arm cases were symptomatic; post-screening, these percentages were 18% in each arm. After almost 17 years of median follow-up, there was no significant reduction in PCa mortality in the intervention compared with the usual care arm. There was a significant increase in Gleason 2-6 disease and a significant reduction in Gleason 8-10 disease in the intervention compared with the usual care arm.

Overall and Multiphasic Findings of the Prostate, Lung, Colorectal and Ovarian (PLCO) Randomized Cancer Screening Trial.

Screening tests are typically evaluated for a single disease, but multiple tests for multiple diseases are performed in practice. The Prostate, Lung, Colorectal and Ovarian (PLCO) cancer screening trial assessed testing for four cancers simultaneously and can be viewed as a multiphasic cancer intervention. This paper presents overall and multiphasic findings of this trial. The PLCO trial was a randomized multi-center trial conducted at ten screening centers in the US. Participants were 76,682 men and 78,215 women ages 55 - 74 and free of the target cancers at trial entry. Screening tests were PSA and digital rectal examination for prostate cancer, chest x-ray for lung cancer, flexible sigmoidoscopy for colorectal cancer, CA125 and transvaginal ultrasound for ovarian cancer. Outcomes and harms of screening were assessed including compliance, test results, incidence, mortality, false positives and overdiagnosis. Screening compliance was 82%, 72,820 (8%) of 906,064 exams were positive, the overall PPV was 4.2% and the cancer detection rate was 3.38/1000. A mortality reduction was observed only for colorectal cancer (RR 0.72, 95% CI 0.61 - 0.85) with no effect on all-cause mortality. Ninety-six percent of positive exams were falsely positive and there was a suggestion of overdiagnosis of prostate and possibly ovarian cancers. Multiphasic testing resulted in 7374 men and 2748 women experiencing multiple false positive results from multiple types of tests. Multiphasic cancer screening led to reduced mortality for one target cancer and imposed a burden on the health care system that included substantial false positives and likely overdiagnosis.

Ovarian cancer screening-ultrasound; impact on ovarian cancer mortality.

Although ovarian cancer (OC) is the most lethal of all female malignancies, debate still exists concerning the benefits and harms of the screening programs and their impact on long-term survival and mortality from the disease. The most widely tested screening strategies have focused on transvaginal ultrasound (TVU) and on algorithms that measure serum levels or interval changes of cancer antigen-125 (CA-125) either individually or in combination. Transvaginal ultrasound can identify size and morphology changes of the ovary that may signal a developing malignancy; yet, it is still accused of having a low specificity. There is preliminary evidence that screening can improve survival, but the impact of screening on mortality from OC is still unclear and warrants further validation. In spite of having many published prospective studies, up to-date, none have been able to demonstrate conclusively a reduction in mortality from OC both in the screened general or high-risk population. Data from the US Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial has not shown survival or mortality benefits in the general population. Most prospective trials have reported a decrease in stage at detection (with the exception of the PLCO trial), thereby allowing treatment to be initiated when the disease is most curable. Research is in progress to develop new diagnostic tests and novel biomarkers, which when used in combination can increase the accuracy and outcomes of screening. In this review article, we will discuss the debate provoked on OC screening programs and the impact of using ultrasound on the reduction of OC-related mortality.