Deep Learning Models for Predicting Malignancy Risk in CT-Detected Pulmonary Nodules: A Systematic Review and Meta-analysis.

BACKGROUND: There has been growing interest in using artificial intelligence/deep learning (DL) to help diagnose prevalent diseases earlier. In this study we sought to survey the landscape of externally validated DL-based computer-aided diagnostic (CADx) models, and assess their diagnostic performance for predicting the risk of malignancy in computed tomography (CT)-detected pulmonary nodules. METHODS: An electronic search was performed in four databases (from inception to 10 August 2023). Studies were eligible if they were peer-reviewed experimental or observational articles comparing the diagnostic performance of externally validated DL-based CADx models with models widely used in clinical practice to predict the risk of malignancy. A bivariate random-effect approach for the meta-analysis on the included studies was used. RESULTS: Seventeen studies were included, comprising 8553 participants and 9884 nodules. Pooled analyses showed DL-based CADx models were 11.6% more sensitive than physician judgement alone, and 14.5% more than clinical risk models alone. They had a similar pooled specificity to physician judgement alone [0.77 (95% CI 0.68-0.84) v 0.81 (95% CI 0.71-0.88)], and were 7.4% more specific than clinical risk models alone. They had superior pooled areas under the receiver operating curve (AUC), with relative pooled AUCs of 1.03 (95% CI 1.00-1.07) and 1.10 (95% CI 1.07-1.13) versus physician judgement and clinical risk models alone, respectively. CONCLUSION: DL-based models are already used in clinical practice in certain settings for nodule management. Our results show their diagnostic performance potentially justifies wider, more routine deployment alongside experienced physician readers to help inform multidisciplinary team decision-making.

Determining the impact of an artificial intelligence tool on the management of pulmonary nodules detected incidentally on CT (DOLCE) study protocol: a prospective, non-interventional multicentre UK study.

INTRODUCTION: In a small percentage of patients, pulmonary nodules found on CT scans are early lung cancers. Lung cancer detected at an early stage has a much better prognosis. The British Thoracic Society guideline on managing pulmonary nodules recommends using multivariable malignancy risk prediction models to assist in management. While these guidelines seem to be effective in clinical practice, recent data suggest that artificial intelligence (AI)-based malignant-nodule prediction solutions might outperform existing models. METHODS AND ANALYSIS: This study is a prospective, observational multicentre study to assess the clinical utility of an AI-assisted CT-based lung cancer prediction tool (LCP) for managing incidental solid and part solid pulmonary nodule patients vs standard care. Two thousand patients will be recruited from 12 different UK hospitals. The primary outcome is the difference between standard care and LCP-guided care in terms of the rate of benign nodules and patients with cancer discharged straight after the assessment of the baseline CT scan. Secondary outcomes investigate adherence to clinical guidelines, other measures of changes to clinical management, patient outcomes and cost-effectiveness. ETHICS AND DISSEMINATION: This study has been reviewed and given a favourable opinion by the South Central-Oxford C Research Ethics Committee in UK (REC reference number: 22/SC/0142).Study results will be available publicly following peer-reviewed publication in open-access journals. A patient and public involvement group workshop is planned before the study results are available to discuss best methods to disseminate the results. Study results will also be fed back to participating organisations to inform training and procurement activities. TRIAL REGISTRATION NUMBER: NCT05389774.

A survey of cancer genome signatures identifies genes connected to distinct chromosomal instability phenotypes.

Certain breast and ovarian cancers are characterised by high levels of chromosomal instability. We established a suite of eleven SNP array-based signatures of various forms of chromosomal instability. To understand what biological mechanisms might underpin these signatures, we generated and assembled genetic-feature data including allele-specific expression, fusion genes, gene expression, methylation, somatic coding mutations and protein expression. For each signature, we extracted a compendium of significantly associated genetic features using machine learning. We established an association between subchromosomal allelic imbalance-based measures and DNA repair genes. Numerical chromosomal instability and chromothripsis were found to have distinct genetic associations but shared a relationship to mitotic processes, while whole-genome doubling was characterised by TP53 mutation, and high AURKA and GINS1 expression. Furthermore, we identified two genetically distinct forms of tandem duplicator phenotypes. These findings identify potentially novel genomic targets for validation and drug development for specific subsets of breast and ovarian cancer.

Determinants of cancer screening awareness and participation among Indonesian women.

BACKGROUND: Cancer screening awareness and participation may be lower in low- and middle-income countries that lack established national screening programmes compared with those that do. We evaluated potential determinants of awareness about and participation in breast and cervical cancer screening, and breast self-examination (BSE) in women using survey data from Indonesia. METHODS: From the fifth Indonesian Family Life Survey (2014-2015), a total of 5397 women aged 40 and older without any history of cancer who responded to questionnaires concerning Pap smears, mammography, and BSE were included. Multilevel modelling was used to assess potential determinants in relation to awareness about Pap smears and mammography, and participation in Pap smears and BSE practice. Multivariable analyses were performed to identify independent predictors of cancer screening. RESULTS: Of the 5397 respondents, 1058 (20%) women were aware of Pap smears, of which 297 had never had the procedure. Only 251 (5%) participants were aware of mammography. A total of 605 (12%) of women reported they performed BSE. Higher education and household expenditure were consistently associated with higher odds of awareness about Pap smears and mammography (e.g. odds ratio [OR] of being aware of Pap smear and mammography: 7.82 (95% CI: 6.30-9.70) and 7.70 (6.19-9.58), respectively, for high school graduates compared to women with less educational attainment in the multivariable models), and participation in Pap smears and BSE. We also identified enabling factors linked with greater cancer screening awareness and participation, including health insurance, shorter distance to health services, and social participation. CONCLUSION: There are socioeconomic disparities in cancer screening awareness and participation among Indonesian women. Our findings may help inform targeted health promotion and screening for cancer in the presence of limited resources.

Bayesian clinical classification from high-dimensional data: Signatures versus variability.

When data exhibit imbalance between a large number d of covariates and a small number n of samples, clinical outcome prediction is impaired by overfitting and prohibitive computation demands. Here we study two simple Bayesian prediction protocols that can be applied to data of any dimension and any number of outcome classes. Calculating Bayesian integrals and optimal hyperparameters analytically leaves only a small number of numerical integrations, and CPU demands scale as O(nd). We compare their performance on synthetic and genomic data to the mclustDA method of Fraley and Raftery. For small d they perform as well as mclustDA or better. For d = 10,000 or more mclustDA breaks down computationally, while the Bayesian methods remain efficient. This allows us to explore phenomena typical of classification in high-dimensional spaces, such as overfitting and the reduced discriminative effectiveness of signatures compared to intra-class variability.

Effects of health and social care spending constraints on mortality in England: a time trend analysis.

OBJECTIVE: Since 2010, England has experienced relative constraints in public expenditure on healthcare (PEH) and social care (PES). We sought to determine whether these constraints have affected mortality rates. METHODS: We collected data on health and social care resources and finances for England from 2001 to 2014. Time trend analyses were conducted to compare the actual mortality rates in 2011-2014 with the counterfactual rates expected based on trends before spending constraints. Fixed-effects regression analyses were conducted using annual data on PES and PEH with mortality as the outcome, with further adjustments for macroeconomic factors and resources. Analyses were stratified by age group, place of death and lower-tier local authority (n=325). Mortality rates to 2020 were projected based on recent trends. RESULTS: Spending constraints between 2010 and 2014 were associated with an estimated 45 368 (95% CI 34 530 to 56 206) higher than expected number of deaths compared with pre-2010 trends. Deaths in those aged ≥60 and in care homes accounted for the majority. PES was more strongly linked with care home and home mortality than PEH, with each £10 per capita decline in real PES associated with an increase of 5.10 (3.65-6.54) (p<0.001) care home deaths per 100 000. These associations persisted in lag analyses and after adjustment for macroeconomic factors. Furthermore, we found that changes in real PES per capita may be linked to mortality mostly via changes in nurse numbers. Projections to 2020 based on 2009-2014 trend was cumulatively linked to an estimated 152 141 (95% CI 134 597 and 169 685) additional deaths. CONCLUSIONS: Spending constraints, especially PES, are associated with a substantial mortality gap. We suggest that spending should be targeted on improving care delivered in care homes and at home; and maintaining or increasing nurse numbers.

Cigarette smoking and telomere length: A systematic review of 84 studies and meta-analysis.

BACKGROUND: Cigarette smoking is a risk factor for ageing-related disease, but its association with biological ageing, indicated by telomere length, is unclear. METHODS: We systematically reviewed evidence evaluating association between smoking status and telomere length. Searches were performed in MEDLINE (Ovid) and EMBASE (Ovid) databases, combining variation of keywords "smoking" and "telomere". Data was extracted for study characteristics and estimates for association between smoking and telomere length. Quality of studies was assessed with a risk of bias score, and publication bias was assessed with a funnel plot. I2 test was used to observe heterogeneity. Meta-analysis was carried out to compare mean difference in telomere length by smoking status, and a dose-response approach was carried out for pack-years of smoking and telomere length. A sensitivity analysis was carried out to examine sources of heterogeneity. RESULTS: A total of 84 studies were included in the review, and 30 among them were included in our meta-analysis. Potential bias was addressed in half of included studies, and there was little evidence of small study bias. Telomere length was shorter among ever smokers compared to never smokers (summary standard mean difference [SMD]: -0.11 (95% CI -0.16 to -0.07)). Similarly, shorter telomere length was found among smokers compared to non-smokers, and among current smokers compared to never or former smokers. Dose-response meta-analysis suggested an inverse trend between pack-years of smoking and telomere length. However, heterogeneity among some analyses was observed. CONCLUSION: Shorter telomeres among ever smokers compared to those who never smoked may imply mechanisms linking tobacco smoke exposure to ageing-related disease.

Effects of economic downturns on child mortality: a global economic analysis, 1981-2010.

OBJECTIVES: To analyse how economic downturns affect child mortality both globally and among subgroups of countries of variable income levels. DESIGN: Retrospective observational study using economic data from the World Bank's Development Indicators and Global Development Finance (2013 edition). Child mortality data were sourced from the Institute for Health Metrics and Evaluation. SETTING: Global. PARTICIPANTS: 204 countries between 1981 and 2010. MAIN OUTCOME MEASURES: Child mortality, controlling for country-specific differences in political, healthcare, cultural, structural, educational and economic factors. RESULTS: 197 countries experienced at least 1 economic downturn between 1981 and 2010, with a mean of 7.97 downturns per country (range 0-21; SD 0.45). At the global level, downturns were associated with significant (p<0.0001) deteriorations in each child mortality measure, in comparison with non-downturn years: neonatal (coefficient: 1.11, 95% CI 0.855 to 1.37), postneonatal (2.00, 95% CI 1.61 to 2.38), child (2.93, 95% CI 2.26 to 3.60) and under 5 years of age (5.44, 95% CI 4.31 to 6.58) mortality rates. Stronger (larger falls in the growth rate of gross domestic product/capita) and longer (lasting 2 years rather than 1) downturns were associated with larger significant deteriorations (p<0.001). During economic downturns, countries in the poorest quartile experienced ∼1½ times greater deterioration in neonatal mortality, compared with their own baseline; a 3-fold deterioration in postneonatal mortality; a 9-fold deterioration in child mortality and a 3-fold deterioration in under-5 mortality, than countries in the wealthiest quartile (p<0.0005). For 1-5 years after downturns ended, each mortality measure continued to display significant deteriorations (p<0.0001). CONCLUSIONS: Economic downturns occur frequently and are associated with significant deteriorations in child mortality, with worse declines in lower income countries.

Inflammatory Differences in Plaque Erosion and Rupture in Patients With ST-Segment Elevation Myocardial Infarction.

BACKGROUND: Plaque erosion causes 30% of ST-segment elevation myocardial infarctions, but the underlying cause is unknown. Inflammatory infiltrates are less abundant in erosion compared with rupture in autopsy studies. We hypothesized that erosion and rupture are associated with significant differences in intracoronary cytokines in vivo. METHODS AND RESULTS: Forty ST-segment elevation myocardial infarction patients with <6 hours of chest pain were classified as ruptured fibrous cap (RFC) or intact fibrous cap (IFC) using optical coherence tomography. Plasma samples from the infarct-related artery and a peripheral artery were analyzed for expression of 102 cytokines using arrays; results were confirmed with ELISA. Thrombectomy samples were analyzed for differential mRNA expression using quantitative real-time polymerase chain reaction. Twenty-three lesions were classified as RFC (58%), 15 as IFC (38%), and 2 were undefined (4%). In addition, 12% (12 of 102) of cytokines were differentially expressed in both coronary and peripheral plasma. I-TAC was preferentially expressed in RFC (significance analysis of microarrays adjusted P<0.001; ELISA IFC 10.2 versus RFC 10.8 log2 pg/mL; P=0.042). IFC was associated with preferential expression of epidermal growth factor (significance analysis of microarrays adjusted P<0.001; ELISA IFC 7.42 versus RFC 6.63 log2 pg/mL, P=0.036) and thrombospondin 1 (significance analysis of microarrays adjusted P=0.03; ELISA IFC 10.4 versus RFC 8.65 log2 ng/mL, P=0.0041). Thrombectomy mRNA showed elevated I-TAC in RFC (P=0.0007) epidermal growth factor expression in IFC (P=0.0264) but no differences in expression of thrombospondin 1. CONCLUSIONS: These results demonstrate differential intracoronary cytokine expression in RFC and IFC. Elevated thrombospondin 1 and epidermal growth factor may play an etiological role in erosion.

Leukemic blasts program bone marrow adipocytes to generate a protumoral microenvironment.

Despite currently available therapies, most patients diagnosed with acute myeloid leukemia (AML) die of their disease. Tumor-host interactions are critical for the survival and proliferation of cancer cells; accordingly, we hypothesize that specific targeting of the tumor microenvironment may constitute an alternative or additional strategy to conventional tumor-directed chemotherapy. Because adipocytes have been shown to promote breast and prostate cancer proliferation, and because the bone marrow adipose tissue accounts for up to 70% of bone marrow volume in adult humans, we examined the adipocyte-leukemia cell interactions to determine if they are essential for the growth and survival of AML. Using in vivo and in vitro models of AML, we show that bone marrow adipocytes from the tumor microenvironment support the survival and proliferation of malignant cells from patients with AML. We show that AML blasts alter metabolic processes in adipocytes to induce phosphorylation of hormone-sensitive lipase and consequently activate lipolysis, which then enables the transfer of fatty acids from adipocytes to AML blasts. In addition, we report that fatty acid binding protein-4 (FABP4) messenger RNA is upregulated in adipocytes and AML when in coculture. FABP4 inhibition using FABP4 short hairpin RNA knockdown or a small molecule inhibitor prevents AML proliferation on adipocytes. Moreover, knockdown of FABP4 increases survival in Hoxa9/Meis1-driven AML model. Finally, knockdown of carnitine palmitoyltransferase IA in an AML patient-derived xenograft model improves survival. Here, we report the first description of AML programming bone marrow adipocytes to generate a protumoral microenvironment.

Circulating Prostate-Specific Antigen and Telomere Length in a Nationally Representative Sample of Men Without History of Prostate Cancer.

BACKGROUND: We investigated the association of prostate-specific antigen (PSA) with leukocyte telomere length, which may be altered in preclinical prostate malignancies. METHODS: This study was based on the 2001-2002 U.S. National Health and Nutrition Examination Survey (NHANES). A subsample of 1,127 men aged 40-85 years without prior history of prostate cancer who provided informed consent and blood samples were selected. Leukocyte telomere length (LTL) relative to standard DNA reference (T/S ratio) was quantified by polymerase chain reaction (PCR). Survey-weighted multivariable linear regression was performed to examine T/S ratio across quintiles of total and free PSA and free-to-total PSA ratio (%fPSA). A sensitivity analysis was performed by excluding men dying from prostate cancer during follow-up through to December 31, 2006. Stratification analyses were carried out to assess any effect modification by age group, race, body mass index (BMI), and levels of C-reactive protein (CRP), a marker of inflammation. RESULTS: Higher total PSA levels were associated to longer LTL, with approximately 8% increase in log-transformed T/S ratio (95% confidence interval [CI]: 2-13%) among men in the highest quintile of total PSA compared to the lowest in the fully adjusted model (Ptrend = 0.01). No significant association was found for free PSA or %fPSA, although nonlinearity between all PSA measures and T/S ratio was indicated. Similar results were found after excluding men who died from prostate cancer during follow-up. We also found the associations between total PSA and T/S ratio to be strongest among non-Hispanic blacks, non-obese men (BMI <30 kg/m2 ), and those with low CRP. However, a significant interaction was only found between total PSA and race/ethnicity (Pinteraction = 0.01). CONCLUSION: Total PSA levels were strongly associated to LTL, particularly among non-Hispanic blacks. Our findings support a potential link between PSA and specific mechanisms contributing to prostate cancer development. Prostate 77:22-32, 2017. © 2016 Wiley Periodicals, Inc.

Profile of the breast cancer susceptibility marker rs4245739 identifies a role for miRNAs.

OBJECTIVE: To determine the influence of the single nucleotide polymorphism (SNP) rs4245739 on the binding and expression of microRNAs and subsequent MDM4 expression and the correlation of these factors with clinical determinants of ER-negative breast cancers. METHODS: FindTar and miRanda were used to detect the manner in which potential microRNAs are affected by the SNP rs4245739-flanking sequence. RNA sequencing data for ER-negative breast cancer from The Cancer Genome Atlas (TCGA) were used to compare the expression of miR-184, miR-191, miR-193a, miR-378, and MDM4 in different rs4245739 genotypes. RESULTS: Comparison of ER-negative cancer patients with and without the expression of miR-191 as well as profile microRNAs (miR-184, miR-191, miR-193a and miR-378 altogether) can differentiate the expression of MDM4 among different rs4245739 genotypes. Although simple genotyping alone did not reveal significant clinical relationships, the combination of genotyping and microRNA profiles was able to significantly differentiate individuals with larger tumor size and lower number of involved lymph nodes (P < 0.05) in the risk group (A allele). CONCLUSIONS: We present two novel methods to analyze SNPs within 3'UTRs that use: (i) a single miRNA marker expression and (ii) an expression profile of miRNAs predicted to bind to the SNP region. We demonstrate that the application of these two methods, in particular the miRNA profile approach, permits detection of new molecular and clinical features related to the rs4245739 variant in ER-negative breast cancer.

PIM1 kinase regulates cell death, tumor growth and chemotherapy response in triple-negative breast cancer.

Triple-negative breast cancers (TNBCs) have poor prognosis and lack targeted therapies. Here we identified increased copy number and expression of the PIM1 proto-oncogene in genomic data sets of patients with TNBC. TNBC cells, but not nonmalignant mammary epithelial cells, were dependent on PIM1 for proliferation and protection from apoptosis. PIM1 knockdown reduced expression of the anti-apoptotic factor BCL2, and dynamic BH3 profiling of apoptotic priming revealed that PIM1 prevents mitochondrial-mediated apoptosis in TNBC cell lines. In TNBC tumors and their cellular models, PIM1 expression was associated with several transcriptional signatures involving the transcription factor MYC, and PIM1 depletion in TNBC cell lines decreased, in a MYC-dependent manner, cell population growth and expression of the MYC target gene MCL1. Treatment with the pan-PIM kinase inhibitor AZD1208 impaired the growth of both cell line and patient-derived xenografts and sensitized them to standard-of-care chemotherapy. This work identifies PIM1 as a malignant-cell-selective target in TNBC and the potential use of PIM1 inhibitors for sensitizing TNBC to chemotherapy-induced apoptotic cell death.

Investigating the associations between adiposity, life course overweight trajectories, and telomere length.

Obesity may accelerate ageing through chronic inflammation. To further examine this association, we assessed current adiposity, adiposity at early adulthood and life course overweight trajectories in relation to leukocyte telomere length (LTL). We included a total of 7,008 nationally representative U.S. residents and collected information on objectively measured body mass index (BMI), waist circumference and percent body fat. BMI at age 25 and overweight trajectories were assessed using self-reported history. Leukocyte telomere length (LTL) relative to a standard DNA reference (T/S ratio) was quantified by polymerase chain reaction (PCR). Linear regression models were used to examine the difference in LTL across adiposity measures at examination, BMI at age 25, and overweight trajectories. A 0.2% decrease in telomere length (95% CI: -0.3 to -0.07%) was observed for every kg/m2 increase in BMI, whereas a unit increase in waist circumference (cm) and percent body fat contributed to a 0.09% and 0.01% decrease in LTL, respectively. Higher BMI and being obese at age 25 contributed to lower LTL at older ages. Associations between weight loss through life course and LTL were observed, which further marked the importance of life course adiposity dynamics as a determinant of ageing.