Age at diagnosis for lung, colon, breast and prostate cancers: An international comparative study.

Differences in the average age at cancer diagnosis are observed across countries. We therefore aimed to assess international variation in the median age at diagnosis of common cancers worldwide, after adjusting for differences in population age structure. We used IARC's Cancer Incidence in Five Continents (CI5) Volume XI database, comprising cancer diagnoses between 2008 and 2012 from population-based cancer registries in 65 countries. We calculated crude median ages at diagnosis for lung, colon, breast and prostate cancers in each country, then adjusted for population age differences using indirect standardization. We showed that median ages at diagnosis changed by up to 10 years after standardization, typically increasing in low- and middle-income countries (LMICs) and decreasing in high-income countries (HICs), given relatively younger and older populations, respectively. After standardization, the range of ages at diagnosis was 12 years for lung cancer (median age 61-Bulgaria vs 73-Bahrain), 12 years for colon cancer (60-the Islamic Republic of Iran vs 72-Peru), 10 years for female breast cancer (49-Algeria, the Islamic Republic of Iran, Republic of Korea vs 59-USA and others) and 10 years for prostate cancer (65-USA, Lithuania vs 75-Philippines). Compared to HICs, populations in LMICs were diagnosed with colon cancer at younger ages but with prostate cancer at older ages (both pLMICS-vs-HICs < 0.001). In countries with higher smoking prevalence, lung cancers were diagnosed at younger ages in both women and men (both pcorr < 0.001). Female breast cancer tended to be diagnosed at younger ages in East Asia, the Middle East and Africa. Our findings suggest that the differences in median ages at cancer diagnosis worldwide likely reflect population-level variation in risk factors and cancer control measures, including screening.

State of the science and future directions for research on HIV and cancer: Summary of a joint workshop sponsored by IARC and NCI.

An estimated 38 million people live with human immunodeficiency virus (HIV) worldwide and are at excess risk for multiple cancer types. Elevated cancer risks in people living with HIV (PLWH) are driven primarily by increased exposure to carcinogens, most notably oncogenic viruses acquired through shared transmission routes, plus acceleration of viral carcinogenesis by HIV-related immunosuppression. In the era of widespread antiretroviral therapy (ART), life expectancy of PLWH has increased, with cancer now a leading cause of co-morbidity and death. Furthermore, the types of cancers occurring among PLWH are shifting over time and vary in their relative burden in different parts of the world. In this context, the International Agency for Research on Cancer (IARC) and the US National Cancer Institute (NCI) convened a meeting in September 2022 of multinational and multidisciplinary experts to focus on cancer in PLWH. This report summarizes the proceedings, including a review of the state of the science of cancer descriptive epidemiology, etiology, molecular tumor characterization, primary and secondary prevention, treatment disparities and survival in PLWH around the world. A consensus of key research priorities and recommendations in these domains is also presented.

Implementation considerations for risk-tailored cancer screening in the population: A scoping review.

BACKGROUND: Risk-tailored screening has emerged as a promising approach to optimise the balance of benefits and harms of existing population cancer screening programs. It tailors screening (e.g., eligibility, frequency, interval, test type) to individual risk rather than the current one-size-fits-all approach of most organised population screening programs. However, the implementation of risk-tailored cancer screening in the population is challenging as it requires a change of practice at multiple levels i.e., individual, provider, health system levels. This scoping review aims to synthesise current implementation considerations for risk-tailored cancer screening in the population, identifying barriers, facilitators, and associated implementation outcomes. METHODS: Relevant studies were identified via database searches up to February 2023. Results were synthesised using Tierney et al. (2020) guidance for evidence synthesis of implementation outcomes and a multilevel framework. RESULTS: Of 4138 titles identified, 74 studies met the inclusion criteria. Most studies in this review focused on the implementation outcomes of acceptability, feasibility, and appropriateness, reflecting the pre-implementation stage of most research to date. Only six studies included an implementation framework. The review identified consistent evidence that risk-tailored screening is largely acceptable across population groups, however reluctance to accept a reduction in screening frequency for low-risk informed by cultural norms, presents a major barrier. Limited studies were identified for cancer types other than breast cancer. CONCLUSIONS: Implementation strategies will need to address alternate models of delivery, education of health professionals, communication with the public, screening options for people at low risk of cancer, and inequity in outcomes across cancer types.

Cancer Stage Compared With Mortality as End Points in Randomized Clinical Trials of Cancer Screening: A Systematic Review and Meta-Analysis.

Importance: Randomized clinical trials of cancer screening typically use cancer-specific mortality as the primary end point. The incidence of stage III-IV cancer is a potential alternative end point that may accelerate completion of randomized clinical trials of cancer screening. Objective: To compare cancer-specific mortality with stage III-IV cancer as end points in randomized clinical trials of cancer screening. Design, Setting, and Participants: This meta-analysis included 41 randomized clinical trials of cancer screening conducted in Europe, North America, and Asia published through February 19, 2024. Data extracted included numbers of participants, cancer diagnoses, and cancer deaths in the intervention and comparison groups. For each clinical trial, the effect of screening was calculated as the percentage reduction between the intervention and comparison groups in the incidence of participants with cancer-specific mortality and stage III-IV cancer. Exposures: Randomization to a cancer screening test or to a comparison group in a clinical trial of cancer screening. Main Outcomes and Measures: End points of cancer-specific mortality and incidence of stage III-IV cancer were compared using Pearson correlation coefficients with 95% CIs, linear regression, and fixed-effects meta-analysis. Results: The included randomized clinical trials tested benefits of screening for breast (n = 6), colorectal (n = 11), lung (n = 12), ovarian (n = 4), prostate (n = 4), and other cancers (n = 4). Correlation between reductions in cancer-specific mortality and stage III-IV cancer varied by cancer type (I2 = 65%; P = .02). Correlation was highest for trials that screened for ovarian (Pearson ρ = 0.99 [95% CI, 0.51-1.00]) and lung (Pearson ρ = 0.92 [95% CI, 0.72-0.98]) cancers, moderate for breast cancer (Pearson ρ = 0.70 [95% CI, -0.26 to 0.96]), and weak for colorectal (Pearson ρ = 0.39 [95% CI, -0.27 to 0.80]) and prostate (Pearson ρ = -0.69 [95% CI, -0.99 to 0.81]) cancers. Slopes from linear regression were estimated as 1.15 for ovarian cancer, 0.75 for lung cancer, 0.40 for colorectal cancer, 0.28 for breast cancer, and -3.58 for prostate cancer, suggesting that a given magnitude of reduction in incidence of stage III-IV cancer produced different magnitudes of change in incidence of cancer-specific mortality (P for heterogeneity = .004). Conclusions and Relevance: In randomized clinical trials of cancer screening, incidence of late-stage cancer may be a suitable alternative end point to cancer-specific mortality for some cancer types, but is not suitable for others. These results have implications for clinical trials of multicancer screening tests.

Assessment of the EarlyCDT-Lung test as an early biomarker of lung cancer in ever-smokers: A retrospective nested case-control study in two prospective cohorts.

The EarlyCDT-Lung test is a blood-based autoantibody assay intended to identify high-risk individuals for low-dose computed tomography lung cancer screening. However, there is a paucity of evidence on the performance of the EarlyCDT-Lung test in ever-smokers. We conducted a nested case-control study within two prospective cohorts to evaluate the risk-discriminatory performance of the EarlyCDT-Lung test using prediagnostic blood samples from 154 future lung cancer cases and 154 matched controls. Cases were selected from those who had ever smoked and had a prediagnostic blood sample <3 years prior to diagnosis. Conditional logistic regression was used to estimate the association between EarlyCDT-Lung test results and lung cancer risk. Sensitivity and specificity of the EarlyCDT-Lung test were calculated in all subjects and subgroups based on age, smoking history, lung cancer stage, sample collection time before diagnosis and year of sample collection. The overall lung cancer odds ratios were 0.89 (95% CI: 0.34-2.30) for a moderate risk EarlyCDT-Lung test result and 1.09 (95% CI: 0.48-2.47) for a high-risk test result compared to no significant test result. The overall sensitivity was 8.4% (95% CI: 4.6-14) and overall specificity was 92% (95% CI: 87-96) when considering a high-risk result as positive. Stratified analysis indicated higher sensitivity (17%, 95% CI: 7.2-32.1) in subjects with blood drawn up to 1 year prior to diagnosis. In conclusion, our study does not support a role of the EarlyCDT-Lung test in identifying the high-risk subjects in ever-smokers for lung cancer screening in the EPIC and NSHDS cohorts.

Prevalence of oral and blood oncogenic human papillomavirus biomarkers among an enriched screening population: Baseline results of the MOUTH study.

BACKGROUND: Human papillomavirus (HPV)-related oropharyngeal cancer screening is being explored in research studies, but strategies to identify an appropriate population are not established. The authors evaluated whether a screening population could be enriched for participants with oncogenic HPV biomarkers using risk factors for oral HPV. METHODS: Participants were enrolled at Johns Hopkins Hospitals and Mount Sinai Icahn School of Medicine. Eligible participants were either men aged 30 years or older who had two or more lifetime oral sex partners and a personal history of anogenital dysplasia/cancer or partners of patients who had HPV-related cancer. Oral rinse and serum samples were tested for oncogenic HPV DNA, RNA, and E6 or E7 antibodies, respectively. Participants with any biomarker were considered at-risk. RESULTS: Of 1108 individuals, 7.3% had any oncogenic oral HPV DNA, and 22.9% had serum antibodies for oncogenic HPV E6 or E7. Seventeen participants (1.5%) had both oral and blood biomarkers. HPV type 16 (HPV16) biomarkers were rarer, detected in 3.7% of participants, including 20 with oral HPV16 DNA and 22 with HPV16 E6 serum antibodies (n = 1 had both). In adjusted analysis, living with HIV (adjusted odds ratio, 2.65; 95% CI, 1.60-4.40) and older age (66-86 vs. 24-45 years; adjusted odds ratio, 1.70; 95% CI, 1.07-2.70) were significant predictors of being at risk. Compared with the general population, the prevalence of oral HPV16 (1.8% vs. 0.9%), any oncogenic oral HPV DNA (7.3% vs. 3.5%), and HPV16 E6 antibodies (2.2% vs. 0.3%) was significantly elevated. CONCLUSIONS: Enrichment by the eligibility criteria successfully identified a population with higher biomarker prevalence, including HPV16 biomarkers, that may be considered for screening trials. Most in this group are still expected to have a low risk of oropharyngeal cancer.

Evaluating multi-cancer early detection tests: an argument for the outcome of recurrence-updated stage.

The advent of multi-cancer early detection (MCED) tests has the potential to revolutionise the diagnosis of cancer, improving patient outcomes through early diagnosis and increased use of curative therapies. The ongoing NHS-Galleri trial is evaluating an MCED test developed by GRAIL, and is using as its primary endpoint the absolute incidence of late-stage cancer. Proponents of this outcome argue that if the test reduces the number of patients with advanced, incurable cancer, it can be reasonably assumed to be benefitting patients by reducing cancer mortality. Here, we argue that this assumption may not always hold due to the phenomenon of micro-metastatic disease, and propose an adjustment to the trial outcome so that it may better reflect the expected effect of the test on cancer mortality.

The influence of postscreening follow-up time and participant characteristics on estimates of overdiagnosis from lung cancer screening trials.

We aimed to explore the underlying reasons that estimates of overdiagnosis vary across and within low-dose computed tomography (LDCT) lung cancer screening trials. We conducted a systematic review to identify estimates of overdiagnosis from randomised controlled trials of LDCT screening. We then analysed the association of Ps (the excess incidence of lung cancer as a proportion of screen-detected cases) with postscreening follow-up time using a linear random effects meta-regression model. Separately, we analysed annual Ps estimates from the US National Lung Screening Trial (NLST) and German Lung Cancer Screening Intervention Trial (LUSI) using exponential decay models with asymptotes. We conducted stratified analyses to investigate participant characteristics associated with Ps using the extended follow-up data from NLST. Among 12 overdiagnosis estimates from 8 trials, the postscreening follow-up ranged from 3.8 to 9.3 years, and Ps ranged from -27.0% (ITALUNG, 8.3 years follow-up) to 67.2% (DLCST, 5.0 years follow-up). Across trials, 39.1% of the variation in Ps was explained by postscreening follow-up time. The annual changes in Ps were -3.5% and -3.9% in the NLST and LUSI trials, respectively. Ps was predicted to plateau at 2.2% for NLST and 9.2% for LUSI with hypothetical infinite follow-up. In NLST, Ps increased with age from -14.9% (55-59 years) to 21.7% (70-74 years), and time trends in Ps varied by histological type. The findings suggest that differences in postscreening follow-up time partially explain variation in overdiagnosis estimates across lung cancer screening trials. Estimates of overdiagnosis should be interpreted in the context of postscreening follow-up and population characteristics.

Comparative performance of lung cancer risk models to define lung screening eligibility in the United Kingdom.

BACKGROUND: The National Health Service England (NHS) classifies individuals as eligible for lung cancer screening using two risk prediction models, PLCOm2012 and Liverpool Lung Project-v2 (LLPv2). However, no study has compared the performance of lung cancer risk models in the UK. METHODS: We analysed current and former smokers aged 40-80 years in the UK Biobank (N = 217,199), EPIC-UK (N = 30,813), and Generations Study (N = 25,777). We quantified model calibration (ratio of expected to observed cases, E/O) and discrimination (AUC). RESULTS: Risk discrimination in UK Biobank was best for the Lung Cancer Death Risk Assessment Tool (LCDRAT, AUC = 0.82, 95% CI = 0.81-0.84), followed by the LCRAT (AUC = 0.81, 95% CI = 0.79-0.82) and the Bach model (AUC = 0.80, 95% CI = 0.79-0.81). Results were similar in EPIC-UK and the Generations Study. All models overestimated risk in all cohorts, with E/O in UK Biobank ranging from 1.20 for LLPv3 (95% CI = 1.14-1.27) to 2.16 for LLPv2 (95% CI = 2.05-2.28). Overestimation increased with area-level socioeconomic status. In the combined cohorts, USPSTF 2013 criteria classified 50.7% of future cases as screening eligible. The LCDRAT and LCRAT identified 60.9%, followed by PLCOm2012 (58.3%), Bach (58.0%), LLPv3 (56.6%), and LLPv2 (53.7%). CONCLUSION: In UK cohorts, the ability of risk prediction models to classify future lung cancer cases as eligible for screening was best for LCDRAT/LCRAT, very good for PLCOm2012, and lowest for LLPv2. Our results highlight the importance of validating prediction tools in specific countries.

Analysis of lung cancer risk model (PLCOM2012 and LLPv2) performance in a community-based lung cancer screening programme.

INTRODUCTION: Low-dose CT (LDCT) screening of high-risk smokers reduces lung cancer (LC) specific mortality. Determining screening eligibility using individualised risk may improve screening effectiveness and reduce harm. Here, we compare the performance of two risk prediction models (PLCOM2012 and Liverpool Lung Project model (LLPv2)) and National Lung Screening Trial (NLST) eligibility criteria in a community-based screening programme. METHODS: Ever-smokers aged 55-74, from deprived areas of Manchester, were invited to a Lung Health Check (LHC). Individuals at higher risk (PLCOM2012 score ≥1.51%) were offered annual LDCT screening over two rounds. LLPv2 score was calculated but not used for screening selection; ≥2.5% and ≥5% thresholds were used for analysis. RESULTS: PLCOM2012 ≥1.51% selected 56% (n=1429) of LHC attendees for screening. LLPv2 ≥2.5% also selected 56% (n=1430) whereas NLST (47%, n=1188) and LLPv2 ≥5% (33%, n=826) selected fewer. Over two screening rounds 62 individuals were diagnosed with LC; representing 87% (n=62/71) of 6-year incidence predicted by mean PLCOM2012 score (5.0%). 26% (n=16/62) of individuals with LC were not eligible for screening using LLPv2 ≥5%, 18% (n=11/62) with NLST criteria and 7% (n=5/62) with LLPv2 ≥2.5%. NLST eligible Manchester attendees had 2.5 times the LC detection rate than NLST participants after two annual screens (≈4.3% (n=51/1188) vs 1.7% (n=438/26 309); p<0.0001). Adverse measures of health, including airflow obstruction, respiratory symptoms and cardiovascular disease, were positively correlated with LC risk. Coronary artery calcification was predictive of LC (adjOR 2.50, 95% CI 1.11 to 5.64; p=0.028). CONCLUSION: Prospective comparisons of risk prediction tools are required to optimise screening selection in different settings. The PLCOM2012 model may underestimate risk in deprived UK populations; further research focused on model calibration is required.

Short Stature and Access to Lung Transplantation in the United States. A Cohort Study.

RATIONALE: Anecdotally, short lung transplant candidates suffer from long waiting times and higher rates of death on the waiting list compared with taller candidates. OBJECTIVES: To examine the relationship between lung transplant candidate height and waiting list outcomes. METHODS: We conducted a retrospective cohort study of 13,346 adults placed on the lung transplant waiting list in the United States between 2005 and 2011. Multivariable-adjusted competing risk survival models were used to examine associations between candidate height and outcomes of interest. The primary outcome was the time until lung transplantation censored at 1 year. MEASUREMENTS AND MAIN RESULTS: The unadjusted rate of lung transplantation was 94.5 per 100 person-years among candidates of short stature (<162 cm) and 202.0 per 100 person-years among candidates of average stature (170-176.5 cm). After controlling for potential confounders, short stature was associated with a 34% (95% confidence interval [CI], 29-39%) lower rate of transplantation compared with average stature. Short stature was also associated with a 62% (95% CI, 24-96%) higher rate of death or removal because of clinical deterioration and a 42% (95% CI, 10-85%) higher rate of respiratory failure while awaiting lung transplantation. CONCLUSIONS: Short stature is associated with a lower rate of lung transplantation and higher rates of death and respiratory failure while awaiting transplantation. Efforts to ameliorate this disparity could include earlier referral and listing of shorter candidates, surgical downsizing of substantially oversized allografts for shorter candidates, and/or changes to allocation policy that account for candidate height.

Logistic analysis of epidemiologic studies with augmentation sampling involving re-stratification and population expansion.

Epidemiologic cross-sectional, case-cohort, or case-control studies often select augmentation samples to supplement an existing (baseline) sample, primarily for the two reasons: (1) to increase the sample sizes from certain subdomains of interest that were not originally considered in the design of the baseline study and (2) to obtain samples from an extension of the target population. To address these two objectives, two-stage stratified sample designs are considered, where the stratification based on the expanded population at the second stage is not nested in the first stage strata. The sample weighting and Taylor linearization variance estimation for the two-stage stratified sample designs, involving re-stratification and population expansion, are provided for estimating population totals and logistic regression coefficients. Results from limited simulation studies and a logistic regression analysis of a study of human papillomavirus serology are provided.

Multilevel correlates of broadly- and narrowly-defined intimate partner violence among pregnant women in Los Angeles.

Studies have identified correlates of intimate partner violence (IPV) during pregnancy at the individual and neighborhood levels, but have used inconsistent definitions of IPV. We aimed to compare correlates based on two IPV definitions: broad (physical, sexual, or psychological violence) and narrow (physical or sexual violence only). Our analysis included 12,358 women in 2,110 census tracts (weighted to represent 269,671 women) who recently gave birth and responded to the Los Angeles Mommy and Baby (LAMB) survey. We linked 2007 and 2010 LAMB data to American Community Survey 2006-2010 census tract data, and conducted separate logistic multilevel analyses to identify correlates of IPV based on each definition. Prevalence of IPV during pregnancy was much higher by the broad (18.3 %) than the narrow definition (3.9 %). No independent neighborhood-level correlates were identified. Some individual-level correlates were associated with both IPV definitions, including substance abuse (OR 3.15, 95 % CI 2.47-4.00 for broad definition; OR 3.60, 95 % CI 2.30-5.64 for narrow definition) and medical problems (OR for ≥3 vs. 0 medical problems 2.03, 95 % CI 1.61-2.55 for broad definition, OR 2.40, 95 % CI 1.54-3.74 for narrow definition). Other correlates associated only with the broad definition, such as car accidents (OR 1.44, 95 % CI 1.04-2.00) and moving during pregnancy (OR 1.35, 95 % CI 1.12-1.62). Differences in correlates of IPV during pregnancy for a broad versus narrow IPV definition may illustrate the situations or mechanisms by which different types of IPV arise. Individual-level characteristics may outweigh neighborhood influences in a diverse population.

Glutathione S-transferase L1 multiplex serology as a measure of cumulative infection with human papillomavirus.

BACKGROUND: Several assays are used to measure type-specific serological responses to human papillomavirus (HPV), including the bead-based glutathione S-transferase (GST)-L1 multiplex serology assay and virus-like particle (VLP)-based ELISA. We evaluated the high-throughput GST-L1, which is increasingly used in epidemiologic research, as a measure of cumulative HPV infection and future immune protection among HPV-unvaccinated women. METHODS: We tested enrollment sera from participants in the control arm of the Costa Rica Vaccine Trial (n = 488) for HPV16 and HPV18 using GST-L1, VLP-ELISA, and two assays that measure neutralizing antibodies (cLIA and SEAP-NA). With statistical adjustment for sampling, we compared GST-L1 serostatus to established HPV seropositivity correlates and incident cervical HPV infection using odds ratios. We further compared GST-L1 to VLP-ELISA using pair-wise agreement statistics and by defining alternate assay cutoffs. RESULTS: Odds of HPV16 GST-L1 seropositivity increased with enrollment age (OR = 1.20 per year, 95%CI 1.03-1.40) and lifetime number of sexual partners (OR = 2.06 per partner, 95%CI 1.49-2.83), with similar results for HPV18. GST-L1 seropositivity did not indicate protection from incident infection over 4 years of follow-up (HPV16 adjusted OR = 1.72, 95%CI 0.95-3.13; HPV18 adjusted OR = 0.38, 95%CI 0.12-1.23). Seroprevalence by GST-L1 (HPV16 and HPV18, respectively) was 5.0% and 5.2%, compared to 19.4% and 23.8% by VLP-ELISA, giving positive agreement of 39.2% and 20.8%. Lowering GST-L1 seropositivity cutoffs improved GST-L1/VLP-ELISA positive agreement to 68.6% (HPV16) and 61.5% (HPV18). CONCLUSIONS: Our data support GST-L1 as a marker of cumulative HPV infection, but not immune protection. At lower seropositivity cutoffs, GST-L1 better approximates VLP-ELISA.