Abstract
Background
A comprehensive examination of the incidence and mortality of subsequent primary cancers (SPCs) among adolescent and young adult (AYA) cancer survivors in the United States is ...lacking.
Methods
Cancer incidence and mortality among 170 404 cancer survivors of 5 or more years who were aged 15-39 years at first primary cancer diagnosis during 1975-2013 in 9 Surveillance, Epidemiology, and End Results registries were compared with those in the general population using standardized incidence ratio (SIR), absolute excess incidence (AEI), standardized mortality ratio (SMR), and absolute excess mortality (AEM).
Results
During a mean follow-up of 14.6 years, 13 420 SPC cases and 5008 SPC deaths occurred among survivors (excluding the same site as index cancer), corresponding to 25% higher incidence (95% confidence interval CI = 1.23 to 1.27, AEI = 10.8 per 10 000) and 84% higher mortality (95% CI = 1.79 to 1.89, AEM = 9.2 per 10 000) than that in the general population. Overall, SPC risk was statistically significantly higher for 20 of 29 index cancers for incidence and 26 for mortality, with the highest SIR among female Hodgkin lymphoma survivors (SIR = 3.05, 95% CI = 2.88 to 3.24, AEI = 73.0 per 10 000) and the highest SMR among small intestine cancer survivors (SMR = 6.97, 95% CI = 4.80 to 9.79, AEM = 64.1 per 10 000). Type-specific SPC risks varied substantially by index cancers; however, SPCs of the female breast, lung, and colorectum combined constituted 36% of all SPC cases and 39% of all SPC deaths, with lung cancer alone representing 11% and 24% of all cases and deaths, respectively.
Conclusion
AYA cancer survivors are almost twice as likely to die from a new primary cancer as the general population, highlighting the need for primary care clinicians to prioritize cancer prevention and targeted surveillance strategies in these individuals.
Abnormal longitudinal values in biomarkers can be a sign of abnormal status or signal development of a disease. Identifying new biomarkers for early and efficient disease detection is crucial for ...disease prevention. Compared to the majority of the healthy general population, abnormal values are located within the tails of the biomarker distribution. Thus, parametric regression models that accommodate abnormal values in biomarkers can better detect the association between biomarkers and disease. In this article, we propose semiparametric Gumbel regression models for (1) longitudinal continuous biomarker outcomes, (2) flexibly modeling the time‐effect on the outcome, and (3) accounting for the measurement error in biomarker measurements. We adopted the EM algorithm in combination with a two‐dimensional grid search to estimate regression parameters and a function of time‐effect. We proposed an efficient asymptotic variance estimator for regression parameter estimates. The proposed estimator is asymptotically unbiased in both theory and simulation studies. We applied the proposed model and two other models to investigate associations between fasting blood glucose biomarkers and potential risk factors from a diabetes ancillary study to the Atherosclerosis Risk in Communities (ARIC) study. The real data application was illustrated by fitting the proposed regression model and graphically evaluating the goodness‐of‐fit value.
Background
This study was aimed at examining the risks of subsequent primary cancers (SPCs) among breast cancer survivors by hormone receptor (HR) status and age at diagnosis.
Methods
Data from 12 ...Surveillance, Epidemiology, and End Results registries were used to identify 431,222 breast cancer survivors (at least 1 year) diagnosed between the ages of 20 and 84 years from 1992 to 2015. Risks of SPCs were measured as the standardized incidence ratio (SIR) and the excess absolute risk (EAR) per 10,000 person‐years. Poisson regression was used to test the difference in SIRs by HR status.
Results
In comparison with the general population, the risk of new cancer diagnoses among survivors was 20% higher for those with HR‐positive cancers (SIR, 1.20; 95% confidence interval CI, 1.19‐1.21; EAR, 23.3/10,000 person‐years) and 44% higher for those with HR‐negative cancers (SIR, 1.44; 95% CI, 1.41‐1.47; EAR, 45.2/10,000 person‐years), with the risk difference between HR statuses statistically significant. The higher risk after HR‐negative cancer was driven by acute nonlymphocytic leukemia and breast, ovarian, peritoneal, and lung cancers. By age at diagnosis, the total EAR per 10,000 person‐years ranged from 15.8 (95% CI, 14.1‐17.5; SIR, 1.11) among late‐onset (age, 50‐84 years) HR‐positive survivors to 69.4 (95% CI, 65.1‐73.7; SIR, 2.24) among early‐onset (age, 20‐49 years) HR‐negative survivors, with subsequent breast cancer representing 73% to 80% of the total EAR. After breast cancer, the greatest EARs were for ovarian cancer among early‐onset HR‐negative survivors, lung cancer among early‐ and late‐onset HR‐negative survivors, and uterine corpus cancer among late‐onset HR‐positive survivors.
Conclusions
Risks of SPCs after breast cancer differ substantially by subtype and age. This suggests that more targeted approaches for cancer prevention and early‐detection strategies are needed in survivorship care planning.
The overall risk of subsequent primary cancers among breast cancer survivors versus the cancer risk in the general population is higher among both hormone receptor (HR)–positive and HR‐negative cancer survivors, although the risk is considerably greater among HR‐negative cancer survivors; this is driven by higher risks for acute nonlymphocytic leukemia and breast, ovarian, peritoneal, and lung cancers. With respect to the age at diagnosis of first breast cancer, the largest excess risk of subsequent primary cancers in both absolute and relative terms occurs among survivors of early‐onset (age, 20‐49 years) HR‐negative breast cancer despite lower cancer incidence rates among younger survivors.
Background
Cancer incidence is higher in men than in women at most shared anatomic sites for currently unknown reasons. The authors quantified the extent to which behaviors (smoking and alcohol use), ...anthropometrics (body mass index and height), lifestyles (physical activity, diet, medications), and medical history collectively explain the male predominance of risk at 21 shared cancer sites.
Methods
Prospective cohort analyses (n = 171,274 male and n = 122,826 female participants; age range, 50–71 years) in the National Institutes of Health‐AARP Diet and Health Study (1995–2011). Cancer‐specific Cox regression models were used to estimate male‐to‐female hazard ratios (HRs). The degree to which risk factors explained the observed male–female risk disparity was quantified using the Peters–Belson method.
Results
There were 26,693 incident cancers (17,951 in men and 8742 in women). Incidence was significantly lower in men than in women only for thyroid and gallbladder cancers. At most other anatomic sites, the risks were higher in men than in women (adjusted HR range, 1.3–10.8), with the strongest increases for bladder cancer (HR, 3.33; 95% confidence interval CI, 2.93–3.79), gastric cardia cancer (HR, 3.49; 95% CI, 2.26–5.37), larynx cancer (HR, 3.53; 95% CI, 2.46–5.06), and esophageal adenocarcinoma (HR, 10.80; 95% CI, 7.33–15.90). Risk factors explained a statistically significant (nonzero) proportion of the observed male excess for esophageal adenocarcinoma and cancers of liver, other biliary tract, bladder, skin, colon, rectum, and lung. However, only a modest proportion of the male excess was explained by risk factors (ranging from 50% for lung cancer to 11% for esophageal adenocarcinoma).
Conclusions
Men have a higher risk of cancer than women at most shared anatomic sites. Such male predominance is largely unexplained by risk factors, underscoring a role for sex‐related biologic factors.
The male predominance of many nonsex‐specific cancers has been explained by differences in exposure prevalence between sexes, but cancer incidence in this study remained significantly higher among men for most sites after a comprehensive adjustment for carcinogenic exposures. These findings suggest a role of sex‐related biologic mechanisms as the major determinants of sex differences in cancer risk.
Electronic health records (EHRs) can be a cost‐effective data source for forming cohorts and developing risk models in the context of disease screening. However, important issues need to be handled: ...competing outcomes, left‐censoring of prevalent disease, interval‐censoring of incident disease, and uncertainty of prevalent disease when accurate disease ascertainment is not conducted at baseline. Furthermore, novel tests that are costly and limited in availability can be conducted on stored biospecimens selected as samples from EHRs by using different sampling fractions. We extend sample‐weighted semiparametric marginal mixture models to estimating competing risks. For flexible modeling of relative risks, a general transformation of the subdistribution hazard function and regression parameters is used. We propose a numerical algorithm for nonparametrically calculating the maximum likelihood estimates for subdistribution hazard functions and regression parameters. Methods for calculating the consistent confidence intervals for relative and absolute risk estimates are presented. The proposed algorithm and methods show reliable finite sample performance through simulation studies. We apply our methods to a cohort assembled from EHRs at a health maintenance organization where we estimate cumulative risk of cervical precancer/cancer and incidence of infection‐clearance by HPV genotype among human papillomavirus (HPV) positive women. There is no significant difference in 3‐year HPV‐clearance rates across different HPV types, but 3‐year cumulative risk of progression‐to‐precancer/cancer from HPV‐16 is relatively higher than the other HPV genotypes.
We propose an extension of Harrell's concordance (C) index to evaluate the prognostic utility of biomarkers for diseases with multiple measurable outcomes that can be prioritized. Our prioritized ...concordance index measures the probability that, given a random subject pair, the subject with the worst disease status as of a time τ has the higher predicted risk. Our prioritized concordance index uses the same approach as the win ratio, by basing generalized pairwise comparisons on the most severe or clinically important comparable outcome. We use an inverse probability weighting technique to correct for study‐specific censoring. Asymptotic properties are derived using U‐statistic properties. We apply the prioritized concordance index to two types of disease processes with a rare primary outcome and a more common secondary outcome. Our simulation studies show that when a predictor is predictive of both outcomes, the new concordance index can gain efficiency and power in identifying true prognostic variables compared to using the primary outcome alone. Using the prioritized concordance index, we examine whether novel clinical measures can be useful in predicting risk of type II diabetes in patients with impaired glucose resistance whose disease status can also regress to normal glucose resistance. We also examine the discrimination ability of four published risk models among ever smokers at risk of lung cancer incidence and subsequent death.
HPV testing is more sensitive than cytology for cervical screening. However, to incorporate HPV tests into screening, risk‐stratification (“triage”) of HPV‐positive women is needed to avoid excessive ...colposcopy and overtreatment. We prospectively evaluated combinations of partial HPV typing (Onclarity, BD) and cytology triage, and explored whether management could be simplified, based on grouping combinations yielding similar 3‐year or 18‐month CIN3+ risks. We typed ∼9,000 archived specimens, taken at enrollment (2007–2011) into the NCI‐Kaiser Permanente Northern California (KPNC) HPV Persistence and Progression (PaP) cohort. Stratified sampling, with reweighting in the statistical analysis, permitted risk estimation of HPV/cytology combinations for the 700,000+‐woman KPNC screening population. Based on 3‐year CIN3+ risks, Onclarity results could be combined into five groups (HPV16, else HPV18/45, else HPV31/33/58/52, else HPV51/35/39/68/56/66/68, else HPV negative); cytology results fell into three risk groups (“high‐grade,” ASC‐US/LSIL, NILM). For the resultant 15 HPV group‐cytology combinations, 3‐year CIN3+ risks ranged 1,000‐fold from 60.6% to 0.06%. To guide management, we compared the risks to established “benchmark” risk/management thresholds in this same population (e.g., LSIL predicted 3‐year CIN3+ risk of 5.8% in the screening population, providing the benchmark for colposcopic referral). By benchmarking to 3‐year risk thresholds (supplemented by 18‐month estimates), the widely varying risk strata could be condensed into four action bands (very high risk of CIN3+ mandating consideration of cone biopsy if colposcopy did not find precancer; moderate risk justifying colposcopy; low risk managed by intensified follow‐up to permit HPV “clearance”; and very low risk permitting routine screening.) Overall, the results support primary HPV testing, with management of HPV‐positive women using partial HPV typing and cytology.
What's new?
Cervical cancer screening includes two elements: cytology and HPV testing. But many women who test positive for HPV won't need further examination; most HPV infections don't lead to cancer. How best to identify those at risk? These authors created a system to simplify risk assessment. By conducting a cohort study to document the likelihood of patients developing CIN3 within three years, they evaluated different patterns of screening results. They were able to stratify risk profiles generated by HPV typing and cytology into four “action bands,” or further screening recommendations, thus balancing the sensitivity of HPV typing with simplicity of implementation.
Originally, 2‐stage group testing was developed for efficiently screening individuals for a disease. In response to the HIV/AIDS epidemic, 1‐stage group testing was adopted for estimating prevalences ...of a single or multiple traits from testing groups of size q, so individuals were not tested. This paper extends the methodology of 1‐stage group testing to surveys with sample weighted complex multistage‐cluster designs. Sample weighted‐generalized estimating equations are used to estimate the prevalences of categorical traits while accounting for the error rates inherent in the tests. Two difficulties arise when using group testing in complex samples: (1) How does one weight the results of the test on each group as the sample weights will differ among observations in the same group. Furthermore, if the sample weights are related to positivity of the diagnostic test, then group‐level weighting is needed to reduce bias in the prevalence estimation; (2) How does one form groups that will allow accurate estimation of the standard errors of prevalence estimates under multistage‐cluster sampling allowing for intracluster correlation of the test results. We study 5 different grouping methods to address the weighting and cluster sampling aspects of complex designed samples. Finite sample properties of the estimators of prevalences, variances, and confidence interval coverage for these grouping methods are studied using simulations. National Health and Nutrition Examination Survey data are used to illustrate the methods.
To identify novel metabolic markers for diabetes development in American Indians.
Using an untargeted high-resolution liquid chromatography-mass spectrometry, we conducted metabolomics analysis of ...study participants who developed incident diabetes (n = 133) and those who did not (n = 298) from 2,117 normoglycemic American Indians followed for an average of 5.5 years in the Strong Heart Family Study. Relative abundances of metabolites were quantified in baseline fasting plasma of all 431 participants. Prospective association of each metabolite with risk of developing type 2 diabetes (T2D) was examined using logistic regression adjusting for established diabetes risk factors.
Seven metabolites (five known and two unknown) significantly predict the risk of T2D. Notably, one metabolite matching 2-hydroxybiphenyl was significantly associated with an increased risk of diabetes, whereas four metabolites matching PC (22:6/20:4), (3S)-7-hydroxy-2',3',4',5',8-pentamethoxyisoflavan, or tetrapeptides were significantly associated with decreased risk of diabetes. A multimarker score comprising all seven metabolites significantly improved risk prediction beyond established diabetes risk factors including BMI, fasting glucose, and insulin resistance.
The findings suggest that these newly detected metabolites may represent novel prognostic markers of T2D in American Indians, a group suffering from a disproportionately high rate of T2D.
HPV testing is replacing cytology for cervical cancer screening because of greater sensitivity and superior reassurance following negative tests for the dozen HPV genotypes that cause cervical ...cancer. Management of women testing positive is unresolved. The need for identification of individual HPV genotypes for clinical use is debated. Also, it is unclear how long to observe persistent infections when precancer is not initially found.
In the longitudinal NCI-Kaiser Permanente Northern California Persistence and Progression (PaP) Study, we observed the clinical outcomes (clearance, progression to CIN3+, or persistence without progression) of 11,573 HPV-positive women aged 30–65 yielding 14,158 type-specific infections.
Risks of CIN3+ progression differed substantially by type, with HPV16 conveying uniquely elevated risk (26% of infections with seven-year CIN3+ risk of 22%). The other carcinogenic HPV types fell into 3 distinct seven-year CIN3+ risk groups: HPV18, 45 (13% of infections, risks >5%, with known elevated cancer risk); HPV31, 33, 35, 52, 58 (39%, risks >5%); and HPV39, 51, 56, 59, 68 (23%, risks <5%). In the absence of progression, HPV clearance rates were similar by type, with 80% of infections no longer detected within three years; persistence to seven years without progression was uncommon. The predictive value of abnormal cytology was most evident for prevalent CIN3+, but less evident in follow-up. A woman's age did not modify risk; rather it was the duration of persistence that was important.
HPV type and persistence are the major predictors of progression to CIN3+; at a minimum, distinguishing HPV16 is clinically important. Dividing the other HPV types into three risk-groups is worth considering.
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