Limited evidence, mostly from studies in Western populations, suggests that the prognostic effects of lifestyle-related risk factors may be molecular subtype-dependent. Here, we examined whether ...pre-diagnostic lifestyle-related risk factors for breast cancer are associated with clinical outcomes by molecular subtype among patients from an understudied Asian population.
In this population-based case series, we evaluated breast cancer risk factors in relation to 10-year all-cause mortality (ACM) and 5-year recurrence by molecular subtype among 3012 women with invasive breast cancer in Sarawak, Malaysia. A total of 579 deaths and 314 recurrence events occurred during a median follow-up period of ~ 24 months. Subtypes (luminal A-like, luminal B-like, HER2-enriched, triple-negative) were defined using immunohistochemical markers for hormone receptors and human epidermal growth factor receptor 2 (HER2) in conjunction with histologic grade. Hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between risk factors and ACM/recurrence were estimated in subtype-specific Cox regression models.
We observed heterogeneity in the relationships between parity/breastfeeding, age at first full-term pregnancy (FFP), family history, body mass index (BMI), and tumor subtype (p value < 0.05). Among luminal A-like patients only, older age at menarche HR (95% CI)
= 2.28 (1.05, 4.95) and being underweight HR
= 3.46 (1.21, 9.89) or overweight HR
3.14 (1.04, 9.50) were associated with adverse prognosis, while parity/breastfeeding HR
= 0.48 (0.27, 0.85) and older age at FFP HR
= 0.20 (0.04, 0.90) were associated with good prognosis. For these women, the addition of age at menarche, parity/breastfeeding, and BMI, provided significantly better fit to a prognostic model containing standard clinicopathological factors alone LRχ
(8df) = 21.78; p value = 0.005. Overall, the results were similar in relation to recurrence.
Our finding that breastfeeding and BMI were associated with prognosis only among women with luminal A-like breast cancer is consistent with those from previously published data in Western populations. Further prospective studies will be needed to clarify the role of lifestyle modification, especially changes in BMI, in improving clinical outcomes for women with luminal A-like breast cancer.
Using population-based data from Sweden, we identified all multiple myeloma (MM) patients (n = 8740) and 5652 monoclonal gammopathy of undetermined significance (MGUS) patients diagnosed between 1986 ...and 2005. We calculated standardized incidence rates (SIRs) for all subsequent hematologic and nonhematologic malignancies for MM patients diagnosed before/after 1995 (introduction of high-dose melphalan/autologous stem cell transplantation HDM-ASCT) and 2000 (introduction of immunomodulatory drugs IMiDs), respectively. MM patients had an 11.51-fold (95% confidence interval: 8.19-15.74) increased risk of acute myeloid leukemia (AML)/myelodysplastic syndromes (MDS); risk was very similar before/after 1995 and 2000, respectively. MGUS patients had an 8.01-fold (5.40-11.43) increased risk of AML/MDS. Risk was confined to IgG/IgA, while no IgM MGUS patients developed AML/MDS; patients with monoclonal-protein (M-protein) concentrations > 1.5 g/dL (SIR = 11.12; 3.61-25.96) had higher risk than those < 1.5 g/dL (SIR = 4.67; 1.71-10.16). An excess risk of nonmelanoma skin cancer was observed subsequent to both MM (SIR = 2.22; 1.74-2.80) and MGUS (SIR = 3.30; 2.76-3.90). Our novel observations of an excess risk for AML/MDS following IgG/IgA (but not IgM) MGUS, and the highest risk associated with M-protein concentrations > 1.5 g/dL, support a role for nontreatment-related factors in plasma cell dyscrasias. AML/MDS risk following MM was the same before/after the introduction of HDM-ASCT. Longer follow-up is needed to characterize second tumor risks in the IMiD era.
Breast, endometrial, and ovarian cancers share some hormonal and epidemiologic risk factors. While several models predict absolute risk of breast cancer, there are few models for ovarian cancer in ...the general population, and none for endometrial cancer.
Using data on white, non-Hispanic women aged 50+ y from two large population-based cohorts (the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial PLCO and the National Institutes of Health-AARP Diet and Health Study NIH-AARP), we estimated relative and attributable risks and combined them with age-specific US-population incidence and competing mortality rates. All models included parity. The breast cancer model additionally included estrogen and progestin menopausal hormone therapy (MHT) use, other MHT use, age at first live birth, menopausal status, age at menopause, family history of breast or ovarian cancer, benign breast disease/biopsies, alcohol consumption, and body mass index (BMI); the endometrial model included menopausal status, age at menopause, BMI, smoking, oral contraceptive use, MHT use, and an interaction term between BMI and MHT use; the ovarian model included oral contraceptive use, MHT use, and family history or breast or ovarian cancer. In independent validation data (Nurses' Health Study cohort) the breast and ovarian cancer models were well calibrated; expected to observed cancer ratios were 1.00 (95% confidence interval CI: 0.96-1.04) for breast cancer and 1.08 (95% CI: 0.97-1.19) for ovarian cancer. The number of endometrial cancers was significantly overestimated, expected/observed = 1.20 (95% CI: 1.11-1.29). The areas under the receiver operating characteristic curves (AUCs; discriminatory power) were 0.58 (95% CI: 0.57-0.59), 0.59 (95% CI: 0.56-0.63), and 0.68 (95% CI: 0.66-0.70) for the breast, ovarian, and endometrial models, respectively.
These models predict absolute risks for breast, endometrial, and ovarian cancers from easily obtainable risk factors and may assist in clinical decision-making. Limitations are the modest discriminatory ability of the breast and ovarian models and that these models may not generalize to women of other races. Please see later in the article for the Editors' Summary.
Despite growing recognition of an etiologic role for inflammation in lung carcinogenesis, few prospective epidemiologic studies have comprehensively investigated the association of circulating ...inflammation markers with lung cancer.
We conducted a nested case-control study (n = 526 lung cancer patients and n = 592 control subjects) within the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Control subjects were matched to lung cancer case patients on age, sex, follow-up time (median = 2.9 years), randomization year, and smoking (pack-years and time since quitting). Serum levels of 77 inflammation markers were measured using a Luminex bead-based assay. Conditional logistic regression and weighted Cox models were used to estimate odds ratios (ORs) and cumulative risks, respectively.
Of 68 evaluable markers, 11 were statistically significantly associated with lung cancer risk (P trend across marker categories < .05), including acute-phase proteins (C-reactive protein CRP, serum amyloid A SAA), proinflammatory cytokines (soluble tumor necrosis factor receptor 2 sTNFRII), anti-inflammatory cytokines (interleukin 1 receptor antagonist IL-1RA), lymphoid differentiation cytokines (interleukin 7 IL-7), growth factors (transforming growth factor alpha TGF-A), and chemokines (epithelial neutrophil-activating peptide 78 ENA 78/CXCL5, monokine induced by gamma interferon MIG/CXCL9, B cell-attracting chemokine 1 BCA-1/CXCL13, thymus activation regulated chemokine TARC/CCL17, macrophage-derived chemokine MDC/CCL22). Elevated marker levels were associated with increased lung cancer risk, with odds ratios comparing the highest vs the lowest group ranging from 1.47 (IL-7) to 2.27 (CRP). For IL-1RA, elevated levels were associated with decreased lung cancer risk (OR = 0.71; 95% confidence interval = 0.51 to 1.00). Associations did not differ by smoking, lung cancer histology, or latency. A cross-validated inflammation score using four independent markers (CRP, BCA-1/CXCL13, MDC/CCL22, and IL-1RA) provided good separation in 10-year lung cancer cumulative risks among former smokers (quartile Q 1 = 1.1% vs Q4 = 3.1%) and current smokers (Q1 = 2.3% vs Q4 = 7.9%) even after adjustment for smoking.
Some circulating inflammation marker levels are associated with prospective lung cancer risk.
We propose and study structured time‐dependent inverse regression (STIR), a novel sufficient dimension reduction model, to analyze longitudinally measured, correlated biomarkers in relation to an ...outcome. The time structure is accommodated in an inverse regression model for the markers that can be applied both to equally and unequally spaced time points for each sample. The inverse regression structure also naturally accommodates retrospectively sampled markers, that is, markers measured in case‐control studies. We estimate the corresponding linear combinations of the markers, the reduction, using least squares. We show that under additional distributional assumptions the reduction contains sufficient information about the outcome. In extensive simulations the STIR linear combinations perform well in predictive models based on samples of realistic size. A Wald‐type test for association of a particular marker with outcome at any time point based on the STIR reduction has better power overall than assessing associations based on logistic or linear regression models that include all longitudinally measured markers as independent predictors. As illustrations we estimate the STIR reductions for a cohort study of diabetes and hyperlipidemia and a case‐control study of brain cancer with multiple longitudinally measured biomarkers. We assess the STIR reductions' predictive performance and identify outcome‐associated biomarkers.
Esophageal squamous cell carcinoma (ESCC) is the predominant histologic subtype of esophageal cancer worldwide. Measurements of circulating inflammation‐related biomarkers may inform etiology or ...provide noninvasive signatures for early diagnosis. We therefore examined levels of inflammation molecules for associations with ESCC risk. Using a case–cohort study designed within the Japan Public Health Center‐based Prospective Study, we measured baseline plasma levels of 92 biomarkers using a multiplex assay in a subcohort of 410 randomly selected participants and 66 participants with incident ESCC (including four cases that occurred in the subcohort). ESCC hazard ratios (HRs) were calculated for 2–4 quantiles of each biomarker by Cox proportional hazards regression models with age as the time metric, adjusted for sex, smoking and alcohol use. Twenty analytes were undetectable in nearly all samples. Of the remaining 72, 12 biomarkers (FGF19, ST1A1, STAMBP, AXIN1, CASP8, NT3, CD6, CDCP1, CD5, SLAMF1, OPG and CSF1) were associated with increased ESCC risk (ptrend < 0.05) with HRs per quantile 1.28–1.65. Seven biomarkers (CXCL6, CCL23, CXCL5, TGFA, CXCL1, OSM and CCL4) were inversely associated with HRs 0.57–0.72. FGF19, CASP8, STAMBP, ST1A1 and CCL‐4 met statistical significance with false discovery rate correction. Associations did not differ <5 vs. ≥5 years between blood collection and ESCC diagnosis. CASP8, STAMBP and ST1A1 were strongly correlated (p < 0.05). Our study expands the range of inflammation molecules associated with the development of this highly lethal neoplasia. Correlations among these novel biomarkers suggest a possible shared pathway. These findings need replication and could further delineate ESCCs molecular mechanisms of carcinogenesis.
What's new?
Chronic inflammation has long been considered an important contributor to carcinogenesis. Circulating levels of inflammation‐related biomarkers may thus provide valuable information regarding cancer etiology, and may eventually aid in the early diagnosis of some cancers. In this study, the authors identified five such proteins that are associated with esophageal squamous cell carcinoma (ESCC) risk. These biomarkers may improve our understanding of ESCC etiology, enhance non‐invasive, molecular diagnostic panels, and may provide potential therapeutic targets.
Our work was motivated by the question whether, and to what extent, well‐established risk factors mediate the racial disparity observed for colorectal cancer (CRC) incidence in the United States. ...Mediation analysis examines the relationships between an exposure, a mediator and an outcome. All available methods require access to a single complete data set with these three variables. However, because population‐based studies usually include few non‐White participants, these approaches have limited utility in answering our motivating question. Recently, we developed novel methods to integrate several data sets with incomplete information for mediation analysis. These methods have two limitations: (i) they only consider a single mediator and (ii) they require a data set containing individual‐level data on the mediator and exposure (and possibly confounders) obtained by independent and identically distributed sampling from the target population. Here, we propose a new method for mediation analysis with several different data sets that accommodates complex survey and registry data, and allows for multiple mediators. The proposed approach yields unbiased causal effects estimates and confidence intervals with nominal coverage in simulations. We apply our method to data from U.S. cancer registries, a U.S.‐population‐representative survey and summary level odds‐ratio estimates, to rigorously evaluate what proportion of the difference in CRC risk between non‐Hispanic Whites and Blacks is mediated by three potentially modifiable risk factors (CRC screening history, body mass index, and regular aspirin use).
Before 1971, several million women were exposed in utero to diethylstilbestrol (DES) given to their mothers to prevent pregnancy complications. Several adverse outcomes have been linked to such ...exposure, but their cumulative effects are not well understood.
We combined data from three studies initiated in the 1970s with continued long-term follow-up of 4653 women exposed in utero to DES and 1927 unexposed controls. We assessed the risks of 12 adverse outcomes linked to DES exposure, including cumulative risks to 45 years of age for reproductive outcomes and to 55 years of age for other outcomes, and their relationships to the baseline presence or absence of vaginal epithelial changes, which are correlated with a higher dose of, and earlier exposure to, DES in utero.
Cumulative risks in women exposed to DES, as compared with those not exposed, were as follows: for infertility, 33.3% vs. 15.5% (hazard ratio, 2.37; 95% confidence interval CI, 2.05 to 2.75); spontaneous abortion, 50.3% vs. 38.6% (hazard ratio, 1.64; 95% CI, 1.42 to 1.88); preterm delivery, 53.3% vs. 17.8% (hazard ratio, 4.68; 95% CI, 3.74 to 5.86); loss of second-trimester pregnancy, 16.4% vs. 1.7% (hazard ratio, 3.77; 95% CI, 2.56 to 5.54); ectopic pregnancy, 14.6% vs. 2.9% (hazard ratio, 3.72; 95% CI, 2.58 to 5.38); preeclampsia, 26.4% vs. 13.7% (hazard ratio 1.42; 95% CI, 1.07 to 1.89); stillbirth, 8.9% vs. 2.6% (hazard ratio, 2.45; 95% CI, 1.33 to 4.54); early menopause, 5.1% vs. 1.7% (hazard ratio, 2.35; 95% CI, 1.67 to 3.31); grade 2 or higher cervical intraepithelial neoplasia, 6.9% vs. 3.4% (hazard ratio, 2.28; 95% CI, 1.59 to 3.27); and breast cancer at 40 years of age or older, 3.9% vs. 2.2% (hazard ratio, 1.82; 95% CI, 1.04 to 3.18). For most outcomes, the risks among exposed women were higher for those with vaginal epithelial changes than for those without such changes.
In utero exposure of women to DES is associated with a high lifetime risk of a broad spectrum of adverse health outcomes. (Funded by the National Cancer Institute.).
Studies have reported young ages at cancer diagnosis in HIV-infected persons and have suggested that HIV accelerates carcinogenesis. However, these comparisons did not account for differences in ...population age structures.
To compare ages at diagnosis for non-AIDS-defining types of cancer that occur in both the AIDS and general populations, after adjustment for differences in age and other demographic characteristics between these populations.
Registry linkage study.
15 HIV/AIDS and cancer registry databases in the United States.
212 055 persons with AIDS enrolled in the U.S. HIV/AIDS Cancer Match Study from 1996 to 2007.
Comparison of age-at-diagnosis distributions for various types of cancer in both the AIDS and general populations, after adjustment for age and other demographic characteristics.
The proportion of person-time contributed by older persons (age ≥65 years) was far smaller in the AIDS population (1.5%) than in the general population (12.5%). Reflecting this difference, the ages at diagnosis for most types of cancer were approximately 20 years younger among persons with AIDS. However, after adjustment for differences in the populations at risk, the median ages at diagnosis in the AIDS and general populations did not differ for most types of cancer (for example, colon, prostate, or breast cancer; all P > 0.100). In contrast, ages at diagnosis of lung (median, 50 vs. 54 years) and anal cancer (median, 42 vs. 45 years) were significantly younger in persons with AIDS than expected in the general population (P < 0.001), and the age at diagnosis of Hodgkin lymphoma was significantly older (median, 42 vs. 40 years; P < 0.001).
Information on other cancer risk factors, including cigarette smoking, was not available. Analysis was restricted to non-Hispanic white and black persons who had AIDS, which could limit the generalizability of the findings to other racial and ethnic groups or to persons with HIV but not AIDS.
For most types of cancer, the age at diagnosis is similar in the AIDS and general populations, after adjustment for the ages of the populations at risk. Modest age differences remained for a few types of cancer, which may indicate either acceleration of carcinogenesis by HIV or earlier exposure to cancer risk factors.
National Cancer Institute.
Background
Biliary tract cancers (BTCs) are rare but deadly cancers (gallbladder cancer GBC, intrahepatic cholangiocarcinoma ICC, extrahepatic cholangiocarcinoma ECC, and ampulla of Vater cancer ...AVC). A recent US study reported increasing GBC incidence among people younger than 45 years and blacks; however, it did not examine trends for other biliary tract sites.
Methods
This study characterized demographic differences in BTC incidence rates and time trends by anatomic site. Population‐based North American Association of Central Cancer Registries data were used to calculate age‐adjusted incidence rates, incidence rate ratios (IRRs), and estimated annual percent changes (eAPCs) for 1999‐2013 by site and demographic group. For sites with significant differences in eAPC by age group, IRRs were compared by age group.
Results
GBC incidence rates declined among women (eAPC, –0.5%/y; P = .01) and all racial/ethnic groups except for non‐Hispanic blacks, among whom rates increased (1.8%/y; P < .0001). Although GBC rates increased among 18‐ to 44‐year‐olds (eAPC, 1.8%/y; P = .01), they decreased among people 45 years old or older (–0.4%/y; P = .009). Sex (P < .0001) and racial/ethnic differences (P = .003 to .02) in GBC incidence were larger for younger people than older people. During this period, ICC (eAPC, 3.2%/y; P < .0001) and ECC rates (1.8%/y; P = .001) steadily increased across sex and racial/ethnic groups. Although AVC incidence rates increased among younger adults (eAPC, 1.8%/y; P = .03) but not older adults (–0.20%/y; P = .30), sex and racial/ethnic IRRs did not differ by age.
Conclusions
Differential patterns of BTC rates and temporal trends have been identified by anatomic site and demographic groups. These findings highlight the need for large pooling projects to evaluate BTC risk factors by anatomic site.
Significant and novel variations in biliary tract cancer incidence rates and trends are identified across anatomic sites by demographic group among adults in the United States between 1999 and 2013. Differences in sex‐ and race/ethnicity‐specific gallbladder cancer incidence rate ratios are larger among younger adults than older adults, and this may reflect underlying differences in the prevalence of and trends in risk factors by demographic group.
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