SwePub
Sök i SwePub databas

  Utökad sökning

Träfflista för sökning "WFRF:(Babic Ana) "

Sökning: WFRF:(Babic Ana)

  • Resultat 1-7 av 7
Sortera/gruppera träfflistan
   
NumreringReferensOmslagsbildHitta
1.
  • Sasamoto, Naoko, et al. (författare)
  • Predicting circulating CA125 levels among healthy premenopausal women
  • 2019
  • Ingår i: Cancer Epidemiology Biomarkers and Prevention. - American Association for Cancer Research. - 1055-9965. ; 28:6, s. 1076-1085
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Cancer antigen 125 (CA125) is the most promising ovarian cancer screening biomarker to date. Multiple studies reported CA125 levels vary by personal characteristics, which could inform personalized CA125 thresholds. However, this has not been well described in premenopausal women. Methods: We evaluated predictors of CA125 levels among 815 premenopausal women from the New England Case Control Study (NEC). We developed linear and dichotomous (-35 U/mL) CA125 prediction models and externally validated an abridged model restricting to available predictors among 473 premenopausal women in the European Prospective Investigation into Cancer and Nutrition Study (EPIC). Results: The final linear CA125 prediction model included age, race, tubal ligation, endometriosis, menstrual phase at blood draw, and fibroids, which explained 7% of the total variance of CA125. The correlation between observed and predicted CA125 levels based on the abridged model (including age, race, and menstrual phase at blood draw) had similar correlation coefficients in NEC (r = 0.22) and in EPIC (r= 0.22). The dichotomous CA125 prediction model included age, tubal ligation, endometriosis, prior personal cancer diagnosis, family history of ovarian cancer, number of miscarriages, menstrual phase at blood draw, and smoking status with AUC of 0.83. The abridged dichotomous model (including age, number of miscarriages, menstrual phase at blood draw, and smoking status) showed similar AUCs in NEC (0.73) and in EPIC (0.78). Conclusions: We identified a combination of factors associated with CA125 levels in premenopausal women. Impact: Our model could be valuable in identifying healthy women likely to have elevated CA125 and consequently improve its specificity for ovarian cancer screening.
  •  
2.
  • Harris, Michael, et al. (författare)
  • Identifying important health system factors that influence primary care practitioners' referrals for cancer suspicion : a European cross-sectional survey.
  • 2018
  • Ingår i: BMJ Open. - BMJ Publishing Group Ltd. - 2044-6055 .- 2044-6055. ; 8:9, s. 1-13
  • Tidskriftsartikel (refereegranskat)abstract
    • <p><strong>OBJECTIVES:</strong> Cancer survival and stage of disease at diagnosis and treatment vary widely across Europe. These differences may be partly due to variations in access to investigations and specialists. However, evidence to explain how different national health systems influence primary care practitioners' (PCPs') referral decisions is lacking.This study analyses health system factors potentially influencing PCPs' referral decision-making when consulting with patients who may have cancer, and how these vary between European countries.</p><p><strong>DESIGN:</strong> Based on a content-validity consensus, a list of 45 items relating to a PCP's decisions to refer patients with potential cancer symptoms for further investigation was reduced to 20 items. An online questionnaire with the 20 items was answered by PCPs on a five-point Likert scale, indicating how much each item affected their own decision-making in patients that could have cancer. An exploratory factor analysis identified the factors underlying PCPs' referral decision-making.</p><p><strong>SETTING:</strong> A primary care study; 25 participating centres in 20 European countries.</p><p><strong>PARTICIPANTS:</strong> 1830 PCPs completed the survey. The median response rate for participating centres was 20.7%.</p><p><strong>OUTCOME MEASURES:</strong> The factors derived from items related to PCPs' referral decision-making. Mean factor scores were produced for each country, allowing comparisons.</p><p><strong>RESULTS:</strong> Factor analysis identified five underlying factors: PCPs' ability to refer; degree of direct patient access to secondary care; PCPs' perceptions of being under pressure; expectations of PCPs' role; and extent to which PCPs believe that quality comes before cost in their health systems. These accounted for 47.4% of the observed variance between individual responses.</p><p><strong>CONCLUSIONS:</strong> Five healthcare system factors influencing PCPs' referral decision-making in 20 European countries were identified. The factors varied considerably between European countries. Knowledge of these factors could assist development of health service policies to produce better cancer outcomes, and inform future research to compare national cancer diagnostic pathways and outcomes.</p>
  •  
3.
  • Harris, Michael, et al. (författare)
  • Identifying important health system factors that influence primary care practitioners' referrals for cancer suspicion : a European cross-sectional survey
  • 2018
  • Ingår i: BMJ Open. - British Medical Journal Publishing Group. - 2044-6055. ; 8:9
  • Tidskriftsartikel (refereegranskat)abstract
    • OBJECTIVES: Cancer survival and stage of disease at diagnosis and treatment vary widely across Europe. These differences may be partly due to variations in access to investigations and specialists. However, evidence to explain how different national health systems influence primary care practitioners' (PCPs') referral decisions is lacking.This study analyses health system factors potentially influencing PCPs' referral decision-making when consulting with patients who may have cancer, and how these vary between European countries. DESIGN: Based on a content-validity consensus, a list of 45 items relating to a PCP's decisions to refer patients with potential cancer symptoms for further investigation was reduced to 20 items. An online questionnaire with the 20 items was answered by PCPs on a five-point Likert scale, indicating how much each item affected their own decision-making in patients that could have cancer. An exploratory factor analysis identified the factors underlying PCPs' referral decision-making. SETTING: A primary care study; 25 participating centres in 20 European countries. PARTICIPANTS: 1830 PCPs completed the survey. The median response rate for participating centres was 20.7%. OUTCOME MEASURES: The factors derived from items related to PCPs' referral decision-making. Mean factor scores were produced for each country, allowing comparisons. RESULTS: Factor analysis identified five underlying factors: PCPs' ability to refer; degree of direct patient access to secondary care; PCPs' perceptions of being under pressure; expectations of PCPs' role; and extent to which PCPs believe that quality comes before cost in their health systems. These accounted for 47.4% of the observed variance between individual responses. CONCLUSIONS: Five healthcare system factors influencing PCPs' referral decision-making in 20 European countries were identified. The factors varied considerably between European countries. Knowledge of these factors could assist development of health service policies to produce better cancer outcomes, and inform future research to compare national cancer diagnostic pathways and outcomes.
4.
  • Klein, Alison P., et al. (författare)
  • Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer
  • 2018
  • Ingår i: Nature Communications. - Nature Publishing Group. - 2041-1723 .- 2041-1723. ; 9
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>In 2020, 146,063 deaths due to pancreatic cancer are estimated to occur in Europe and the United States combined. To identify common susceptibility alleles, we performed the largest pancreatic cancer GWAS to date, including 9040 patients and 12,496 controls of European ancestry from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4). Here, we find significant evidence of a novel association at rs78417682 (7p12/TNS3, P = 4.35 x 10(-8)). Replication of 10 promising signals in up to 2737 patients and 4752 controls from the PANcreatic Disease ReseArch (PAN-DoRA) consortium yields new genome-wide significant loci: rs13303010 at 1p36.33 (NOC2L, P = 8.36 x 10(-14)), rs2941471 at 8q21.11 (HNF4G, P = 6.60 x 10(-10)), rs4795218 at 17q12 (HNF1B, P = 1.32 x 10(-8)), and rs1517037 at 18q21.32 (GRP, P = 3.28 x 10(-8)). rs78417682 is not statistically significantly associated with pancreatic cancer in PANDoRA. Expression quantitative trait locus analysis in three independent pancreatic data sets provides molecular support of NOC2L as a pancreatic cancer susceptibility gene.</p>
5.
  • Sasamoto, Naoko, et al. (författare)
  • Development and validation of circulating CA125 prediction models in postmenopausal women
  • 2019
  • Ingår i: Journal of Ovarian Research. - BioMed Central. - 1757-2215 .- 1757-2215. ; 12:1
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Background: Cancer Antigen 125 (CA125) is currently the best available ovarian cancer screening biomarker. However, CA125 has been limited by low sensitivity and specificity in part due to normal variation between individuals. Personal characteristics that influence CA125 could be used to improve its performance as screening biomarker.</p><p>Methods: We developed and validated linear and dichotomous (&gt;= 35 U/mL) circulating CA125 prediction models in postmenopausal women without ovarian cancer who participated in one of five large population-based studies: Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO, n = 26,981), European Prospective Investigation into Cancer and Nutrition (EPIC, n = 861), the Nurses' Health Studies (NHS/NHSII, n = 81), and the New England Case Control Study (NEC, n = 923). The prediction models were developed using stepwise regression in PLCO and validated in EPIC, NHS/NHSII and NEC. Result The linear CA125 prediction model, which included age, race, body mass index (BMI), smoking status and duration, parity, hysterectomy, age at menopause, and duration of hormone therapy (HT), explained 5% of the total variance of CA125. The correlation between measured and predicted CA125 was comparable in PLCO testing dataset (r = 0.18) and external validation datasets (r = 0.14). The dichotomous CA125 prediction model included age, race, BMI, smoking status and duration, hysterectomy, time since menopause, and duration of HT with AUC of 0.64 in PLCO and 0.80 in validation dataset.</p><p>Conclusions: The linear prediction model explained a small portion of the total variability of CA125, suggesting the need to identify novel predictors of CA125. The dichotomous prediction model showed moderate discriminatory performance which validated well in independent dataset. Our dichotomous model could be valuable in identifying healthy women who may have elevated CA125 levels, which may contribute to reducing false positive tests using CA125 as screening biomarker.</p>
6.
  • Sasamoto, Naoko, et al. (författare)
  • Development and validation of circulating CA125 prediction models in postmenopausal women
  • 2019
  • Ingår i: Journal of Ovarian Research. - BioMed Central (BMC). - 1757-2215. ; 12:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Cancer Antigen 125 (CA125) is currently the best available ovarian cancer screening biomarker. However, CA125 has been limited by low sensitivity and specificity in part due to normal variation between individuals. Personal characteristics that influence CA125 could be used to improve its performance as screening biomarker. Methods: We developed and validated linear and dichotomous (≥35 U/mL) circulating CA125 prediction models in postmenopausal women without ovarian cancer who participated in one of five large population-based studies: Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO, n = 26,981), European Prospective Investigation into Cancer and Nutrition (EPIC, n = 861), the Nurses' Health Studies (NHS/NHSII, n = 81), and the New England Case Control Study (NEC, n = 923). The prediction models were developed using stepwise regression in PLCO and validated in EPIC, NHS/NHSII and NEC. Result: The linear CA125 prediction model, which included age, race, body mass index (BMI), smoking status and duration, parity, hysterectomy, age at menopause, and duration of hormone therapy (HT), explained 5% of the total variance of CA125. The correlation between measured and predicted CA125 was comparable in PLCO testing dataset (r = 0.18) and external validation datasets (r = 0.14). The dichotomous CA125 prediction model included age, race, BMI, smoking status and duration, hysterectomy, time since menopause, and duration of HT with AUC of 0.64 in PLCO and 0.80 in validation dataset. Conclusions: The linear prediction model explained a small portion of the total variability of CA125, suggesting the need to identify novel predictors of CA125. The dichotomous prediction model showed moderate discriminatory performance which validated well in independent dataset. Our dichotomous model could be valuable in identifying healthy women who may have elevated CA125 levels, which may contribute to reducing false positive tests using CA125 as screening biomarker.
7.
  • Sasamoto, Naoko, et al. (författare)
  • Predicting Circulating CA125 Levels among Healthy Premenopausal Women
  • 2019
  • Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - American Association for Cancer Research (AACR). - 1055-9965 .- 1538-7755. ; 28:6, s. 1076-1085
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Background: Cancer antigen 125 (CA125) is the most promising ovarian cancer screening biomarker to date. Multiple studies reported CA125 levels vary by personal characteristics, which could inform personalized CA125 thresholds. However, this has not been well described in premenopausal women. Methods: We evaluated predictors of CA125 levels among 815 premenopausal women from the New England Case Control Study (NEC). We developed linear and dichotomous (&gt;= 35 U/mL) CA125 prediction models and externally validated an abridged model restricting to available predictors among 473 premenopausal women in the European Prospective Investigation into Cancer and Nutrition Study (EPIC). Results: The final linear CA125 prediction model included age, race, tubal ligation, endometriosis, menstrual phase at blood draw, and fibroids, which explained 7% of the total variance of CA125. The correlation between observed and predicted CA125 levels based on the abridged model (including age, race, and menstrual phase at blood draw) had similar correlation coefficients in NEC (r = 0.22) and in EPIC (r = 0.22). The dichotomous CA125 prediction model included age, tubal ligation, endometriosis, prior personal cancer diagnosis, family history of ovarian cancer, number of miscarriages, menstrual phase at blood draw, and smoking status with AUC of 0.83. The abridged dichotomous model (including age, number of miscarriages, menstrual phase at blood draw, and smoking status) showed similar AUCs in NEC (0.73) and in EPIC (0.78). Conclusions: We identified a combination of factors associated with CA125 levels in premenopausal women. Impact: Our model could be valuable in identifying healthy women likely to have elevated CA125 and consequently improve its specificity for ovarian cancer screening.</p>
  •  
Skapa referenser, mejla, bekava och länka
  • Resultat 1-7 av 7
 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy