コーパス検索結果 (1語後でソート)
通し番号をクリックするとPubMedの該当ページを表示します
1 h history of being studied in the context of cancer risk.
2 abetes risk reduction diet (DRRD) and breast cancer risk.
3 high ACR, were independently associated with cancer risk.
4 reduce anal high-risk HPV infection and anal cancer risk.
5 se functional SNPs were associated with lung cancer risk.
6 identified as potential mediators of breast cancer risk.
7 ulin-like growth factors may increase breast cancer risk.
8 germline mutations are known to affect lung cancer risk.
9 and cancer, whereas healthy diets can reduce cancer risk.
10 ls and assessed their contribution to breast cancer risk.
11 rrelates for clinical prediction of prostate cancer risk.
12 nd the effects of ovarian function on breast cancer risk.
13 tifying how treatment and eradication affect cancer risk.
14 Immunodeficiency is associated with cancer risk.
15 HIV-1 RNA level (HIV RNA) best predict anal cancer risk.
16 between immune cell composition and prostate cancer risk.
17 elationship between pleural plaques and lung cancer risk.
18 hol consumption and overall or site-specific cancer risk.
19 sociated with a ~2-fold increase in prostate cancer risk.
20 anges during pregnancy with regard to breast cancer risk.
21 an's reproductive years may increase ovarian cancer risk.
22 e potential benefits on smoking-related lung cancer risk.
23 between long-term oral contraceptive use and cancer risk.
24 peated shows a causal relationship with skin cancer risk.
25 nsistently associated with increased bladder cancer risk.
26 rapeutic targets, and determining hereditary cancer risk.
27 populations at an average underlying breast cancer risk.
28 , is associated with increased human gastric cancer risk.
29 sed differences in smoking behaviors or lung cancer risk.
30 her insights into the links between diet and cancer risk.
31 differentiation, transformation, and breast cancer risk.
32 KIAA0930 as a novel candidate gene for lung cancer risk.
33 breast microenvironment may increase breast cancer risk.
34 obesity-lifestyle factors, affecting breast cancer risk.
35 onventional risk factors in modifying breast cancer risk.
36 hanisms by which circadian disruption alters cancer risk.
37 city and aggressiveness, and increase breast cancer risk.
38 e relationship between bariatric surgery and cancer risk.
39 king mLOY an attractive candidate marker for cancer risk.
40 -penetrance genetic factors increase thyroid cancer risk.
41 igarettes, including any potential effect on cancer risk.
42 y the effect of MC diagnosis and severity on cancer risk.
43 egatively associated with both MD and breast cancer risk.
44 forts should be prioritised to reduce future cancer risk.
45 olangitis, inflammatory diseases with a high cancer risk.
46 s that higher estrogen levels decrease liver cancer risk.
47 umption was positively related to colorectal cancer risk.
48 nisms through which bariatric surgery lowers cancer risk.
49 ents with ER-positive and ER-negative breast cancer risk.
50 putative risk factor (OR(SD)) for colorectal cancer risk.
51 and lifestyle factors to reduce their breast cancer risk.
52 ing variants, some of which may not increase cancer risk.
53 as a novel player linking obesity and breast cancer risk.
54 ctors, such as the oncoprotein CagA, augment cancer risk.
55 ppropriate monitoring for reproductive organ cancer risk.
56 mutant allele does not cause any increase in cancer risk.
57 entive role of statins in epithelial ovarian cancer risk.
58 henotypes and their associations with breast cancer risk.
59 markers for identifying PLWH at higher anal cancer risk.
60 M of obese mammary tissue may enhance breast cancer risk.
61 cose (IFG) and their combined effects on the cancer risk.
62 e phenotypes are unique to cases with higher cancer risk.
63 0) was identified for hypopharynx and larynx cancer risk.
64 screening and preventive measures to reduce cancer risk.
65 k and IFG, and their combined effects on the cancer risk.
66 tissues as we age are major determinants of cancer risk.
67 ion, which may influence HIV acquisition and cancer risks.
68 s between relative counts of immune cell and cancer risks.
69 as associated with a 12% reduction of breast cancer risk (adjusted odds ratio [OR] 0.88; 95% confiden
80 ulatory and cytotoxic T cells in determining cancer risk among healthy individuals.See related commen
81 f MITF(E318K)'s contribution to non-melanoma cancer risk among individuals with low inherited risks o
85 se of powder in the genital area and ovarian cancer risk among women with a patent reproductive tract
86 tion between height and premenopausal breast cancer risk and a negative association with overall adip
87 ological evidence suggests that diet affects cancer risk and also substantially alters therapeutic ou
89 ed HRs and 95% CIs for total invasive breast cancer risk and by estrogen receptor (ER), progesterone
90 se these features are associated with breast cancer risk and can improve detecting women at short-ter
91 change, which are all associated with breast cancer risk and can indicate women at short-term risk.
94 vestigated the impact of pre-hypertension on cancer risk and IFG, and their combined effects on the c
98 .33, and 2p23.1) associated with oral cavity cancer risk and oropharyngeal cancer risk, respectively.
100 to identify associations between colorectal cancer risk and patient and adenoma characteristics (dia
102 insulin have been associated with increased cancer risk and progression in epidemiology studies.
103 alpha (ER) plays a major role in endometrial cancer risk and progression, however, the molecular mech
104 e association between differentiated thyroid cancer risk and the energy-adjusted Dietary Inflammatory
106 2A expression may alter smoking-related lung cancer risk and tissue damage from other inhaled toxins.
108 hibition confers an irreversible increase in cancer risk and uncovers a biphasic role of autophagy in
109 odels, we assessed associations between anal cancer risk and various time-updated CD4 and HIV RNA mea
110 BRCA1/2) poses tissue-specific variations in cancer risks and primarily associate with familial breas
111 FOXP3(+) regulatory T cells (Tregs) and lung cancer risk, and significant inverse associations were o
112 specialists such as dentists screen for oral cancer risk, and then they refer high-risk patients to s
115 ukemia, Impact of Remote Familial Colorectal Cancer Risk Assessment and Counseling (Family CARE Proje
116 cilitates gene-informed molecular diagnosis, cancer risk assessment and gene-specific clinical manage
117 tudy illustrates the potential for improving cancer risk assessment by integrating genetic risk score
119 t risks [IURs]) available from the USEPA non-cancer risk assessments and cancer risk assessments were
120 om the USEPA non-cancer risk assessments and cancer risk assessments were developed for some of these
122 Further studies are required to estimate cancer risk associated with these hypomorphic variants.
123 ng carcinogen, little is known regarding the cancer risks associated with low levels of exposure and
124 ed to address current knowledge gaps in lung cancer risks associated with low levels of occupational
128 emerging evidence of variability in gastric cancer risk between families with HDGC, the growing capa
131 h HIV are a global population with increased cancer risk but their access to modern immunotherapies f
133 fish consumption with upper gastrointestinal cancer risk, but the associations with n-3 and n-6 polyu
134 netic variants that are associated with lung cancer risk, but the biological mechanisms underlying th
135 le factors have been associated with gastric cancer risk, but the extent to which an increased geneti
136 t that physical activity might reduce breast cancer risk by about 20% for women across the risk conti
137 cal impact of strategies focused on lowering cancer risk by preventing premature aging or promoting h
139 and multiomics nanotechnology-based prostate cancer risk delineation can enable refinement of prostat
141 nd cancers and can be used as biomarkers for cancer risk determination, early detection of cancer and
143 HQ(s)) > 1; hazard index (HI) ~6; the excess cancer risk (ECR) > 1 x 10(-6)) and, therefore, comprehe
144 tamin D may have a protective effect on skin cancer risk, epidemiologic studies investigating the inf
145 d in everyday products contribute to raising cancer risks, especially for vulnerable populations such
146 r adjusting for family ascertainment, breast cancer risk estimates on the basis of multiple case fami
149 odels and further adjusted for known ovarian cancer risk factors (e.g., hormonal factors) and health
150 ing the underlying molecular basis of breast cancer risk factors and improving primary and secondary
151 wed efforts to reduce exposure to the kidney cancer risk factors and to improve the prevention and th
153 seeking to decrease exposure to known breast cancer risk factors are warranted in all world regions t
154 continues to rise, and few modifiable breast cancer risk factors have been identified, especially for
156 ated with these DNA methylation-based breast cancer risk factors, and the observed associations are u
159 esophageal adenocarinoma, and screening for cancer risk focuses upon histologic assessment of dyspla
160 cal activity is associated with lower breast cancer risk for average-risk women, it is not known if t
161 showed negative association with colorectal cancer risk for cases with microsatellite stable/MSI-low
162 sical activity in adulthood may lower breast cancer risk for women across the spectrum of familial ri
163 ize and visualize functional consequences of cancer risk gene and miRNA pairs while analyzing the tum
169 vegetables, and fiber intake with colorectal cancer risk have been shown in many, but not all epidemi
171 inhibition was associated with lower ovarian cancer risk (hazard ratio, 0.69 [95% CI, 0.51-0.93]; P =
172 erum retinol was not associated with overall cancer risk (highest vs. lowest quintile: hazard ratio (
173 oposed explanations for this heightened skin cancer risk; however, the exact mechanism driving skin c
174 ntile was associated with a 20% lower breast cancer risk (HR, 0.80; 95% confidence interval, 0.68-0.9
175 tion was considerable in this area (lifetime cancer risk (ILCR) > 1 x 10(-5); hazard quotients (HQ(s)
177 longitudinal phthalate exposures and breast cancer risk in a Danish nationwide cohort, using redeeme
178 between HOXB13 germline mutations and breast cancer risk in a previous study consisting of 3,270 fami
179 een air pollution, PM components, and breast cancer risk in a United States-wide prospective cohort.
180 fied MD loci also are associated with breast cancer risk in an independent meta-analysis (P < 0.05).
181 -ancestry women is also predictive of breast cancer risk in Asian women and can help in developing ri
182 ur types associated with increased heritable cancer risk in BRCA1/2 carriers (BRCA-associated cancer
186 consistently associated with elevated breast cancer risk in cohort studies and are associated with ri
187 h have been shown to be predictive of future cancer risk in cohort studies and could, therefore, pote
189 l plaques did not confer any additional lung cancer risk in either cohort (cohort 1: HR, 1.03; 95% co
190 ores (PRS) have been shown to predict breast cancer risk in European women, but their utility in Asia
199 ship between incessant ovulation and ovarian cancer risk in order to identify mechanisms of carcinoge
202 adiponectin receptor agonist, suppress colon cancer risk in part by reducing the number of Lgr5(+) st
204 E ADVICE 16: Patients should be counseled on cancer risk in the absence of BET, as well as after BET,
205 rent models that suggest that persistence of cancer risk in the absence of continued carcinogen expos
206 be used as a chemopreventive agent to reduce cancer risk in women with high mammographic density.
207 ciated (P trend < 0.01) with increasing lung cancer risks in nonsilicotics and in current, former, an
212 w that, in addition to accidental mutations, cancer risk is determined by networks of individual gene
215 us (HIV; PLWH) have a markedly elevated anal cancer risk, largely due to loss of immunoregulatory con
217 D-adherence was associated with lower breast cancer risk, likely mediated by less weight gain with a
218 y remains the recommended option for gastric cancer risk management in pathogenic CDH1 variant carrie
220 fects of smoking and silica exposure on lung cancer risks.Methods: Subjects from 14 case-control stud
221 lume changes - although not linked to breast cancer risk - might be an interesting phenotype in this
222 mparisons were made to an established breast cancer risk model that included breast density (Tyrer-Cu
224 was associated with a modestly lower breast cancer risk (MVHRQ5vsQ1: 0.89; 95% CI: 0.84, 0.95; P-tre
225 ar intake was associated with higher overall cancer risk (n = 2503 cases; HR for quartile 4 compared
226 atin treatment, were associated with overall cancer risk (odds ratio [OR] per one standard deviation
227 st cancer cases, the PRS modifies the breast cancer risk of two high-impact frameshift risk variants.
228 ons, anticancer defenses are too weak, given cancer risk, older females could not pursue their reprod
230 27 for >= 2 versus < 1 times/day) or overall cancer risk (OR 0.93; 95% CI 0.75-1.16; P = 0.52 for >=
232 -cholesterol was not associated with overall cancer risk (OR per standard deviation increase 1.01, 95
234 sociation between CRP and epithelial ovarian cancer risk overall, by histologic subtype and by partic
235 ons between total and added sugar intake and cancer risk (overall, breast, and prostate), taking into
239 sition were captured using the BROCA Agilent cancer risk panel followed by massively parallel sequenc
241 carcinoma and may also contribute to breast cancer risk, particularly among patients who develop dis
242 sed here could provide new insights into how cancer risk persists following cessation of carcinogenic
244 at has been suspected to increase colorectal cancer risk potentially via endogenous formation of carc
245 ad been done using cohorts for common breast cancer risk prediction models, and those that have been
246 ment, we discuss the current state of breast cancer risk prediction, risk-stratified prevention and e
249 erum retinol was not associated with overall cancer risk (Q5 vs. Q1: HR=0.97, 95% CI=0.91,1.03, p-tre
254 idate target genes at 139 independent breast cancer risk signals and explore the functional mechanism
256 lifestyle as synergistic factors for breast cancer risk, suggesting lifestyle changes can prevent br
257 man leukocyte antigen loci for oropharyngeal cancer risk, suggesting that immunologic mechanisms are
258 ure and smoking was observed on overall lung cancer risks; superadditive effects were observed in ris
259 is more strongly associated with pancreatic cancer risk than BMI at older ages and underscore the im
260 is more strongly associated with pancreatic cancer risk than BMI at older ages, and they underscore
261 st were generally better predictors for anal cancer risk than their corresponding more recent measure
264 ting variants in PALB2 are known to increase cancer risk, the interpretation of missense variants of
265 and p.R217C were not associated with breast cancer risk, the risk estimation for p.R217C was not ver
266 ary mismatch between anticancer defenses and cancer risks, the evolution of prolonged life after repr
269 d on creatinine and cystatin C) and ACR with cancer risk using Cox regression models adjusted for pot
271 metabolic equivalents per week) with breast cancer risk using multivariable Cox proportional hazards
272 (self-reported by questionnaire) with breast cancer risk using the Prospective Family Study Cohort, w
273 ity to estimate an individual woman's breast cancer risk using validated risk assessment models, and
275 (for adults) and 1.12% (for children) of the cancer risk values surpassed the specified limits at Iju
276 sed the specified limits at Iju, whereas the cancer risk values were considerably lesser at Atan.
277 e association studies have identified breast cancer risk variants in over 150 genomic regions, but th
281 rrying MC1R variants imparting elevated skin cancer risk was consistent across quartiles of European,
282 ociation between c-peptide levels and breast cancer risk was evident in only women age >=51 years (OR
283 ared with the general population, colorectal cancer risk was higher or comparable only for individual
286 In addition, significant associations with cancer risk were also observed for added sugars, free su
288 carbonyl compounds and estimated changes in cancer risk were assessed by production of aerosols gene
289 index, breast density, and estimated breast cancer risk were assessed by using Fisher exact, chi(2),
291 itive associations between E-DII and thyroid cancer risk were observed (comparing extreme tertiles, o
292 ociations between adult adiposity and breast cancer risk were observed in adjusted models (body mass
294 and population-level differences in prostate cancer risk were revealed using a novel genotyping array
295 published by the USEPA, no unacceptable non-cancer risks were evident except under extremely high co
297 ombination effect of BP and fasting glucose, cancer risks were serially increased with an increase in
298 how gene-environment interactions influence cancer risk when the initiating genetic defect responsib
299 etween HOXB13 mutations and increased breast cancer risk within 81 studies of the international Breas