Relationship between formulaic breast volume and risk of breast cancer based on linear measurements

Abstract Background Whether breast volume is a risk factor for breast cancer is controversial. This study aimed to evaluate whether a significant association between breast volume and risk of breast cancer, based on linear measurements, was present by applying propensity score matching (PSM). Methods The study was designed as a hospital-based case-control study. Between March 2018 and May 2019, 208 cases and 340 controls were retrospectively reviewed. Information on menarche, smoking, feeding mode, oral contraceptives, reproductive history and family history was obtained through a structured questionnaire. Breast volume was calculated using a formula based on linear measurements of breast parameters. Cox regression and PSM were used to estimate odds ratios and 95% confidence intervals for breast cancer using risk factors adjusted for potential confounders. Results There was a significant difference in breast volume between the two groups before propensity score matching (P = 0.014). Binary logistic regression showed that the risk of breast cancer was slightly higher in the case group with larger breast volumes than in the control group(P = 0.009, OR = 1.002, 95%CI:1.000 ~ 1.003). However, there was no significant statistical difference between the two groups using an independent sample Mann-Whitney U test (P = 0.438) or conditional logistic regression (P = 0.446). Conclusions After PSM for potential confounding factors, there is no significant difference in breast volume estimated by BREAST-V formula between the case group and the control group. The risk of breast cancer may not be related to breast volume in Chinese women.

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Relationship between formulaic breast volume and risk of breast cancer based on linear measurement

10.21203/rs.3.rs-23397/v4 ◽

2020 ◽

Author(s):

Xiaoxia Li ◽

Chunlan Zhou ◽

Yanni Wu ◽

Xiaohong Chen

Keyword(s):

Breast Cancer ◽

Logistic Regression ◽

Propensity Score ◽

Propensity Score Matching ◽

Conditional Logistic Regression ◽

Control Group ◽

Case Group ◽

Breast Volume ◽

Linear Measurements ◽

Significant Difference

Abstract Background: Whether breast volume is a risk factor for breast cancer is controversial. This study aimed to evaluate whether a significant association between breast volume and risk of breast cancer, based on linear measurements, was present by applying propensity score matching (PSM).Methods: The study was designed as a hospital-based case-control study. Between March 2018 and May 2019, 208 cases and 340 controls were retrospectively reviewed. Information on menarche, smoking, feeding mode, oral contraceptives, reproductive history and family history was obtained through a structured questionnaire. Breast volume was calculated using a formula based on linear measurements of breast parameters. Cox regression and PSM were used to estimate odds ratios and 95% confidence intervals for breast cancer using risk factors adjusted for potential confounders.Results: There was a significant difference in breast volume between the two groups before propensity score matching(P = 0.014) . Binary logistic regression showed that the risk of breast cancer was slightly higher in the case group with larger breast volumes than in the control group（P = 0.009, OR = 1.002， 95%CI：1.000~1.003). However, there was no significant statistical difference between the two groups using an independent sample Mann-Whitney U test (P = 0.438) or conditional logistic regression (P = 0.446).Conclusions: After PSM for potential confounding factors, there is no significant difference in breast volume estimated by BREAST-V formula between the case group and the control group. The risk of breast cancer may not be related to breast volume in Chinese women.

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Relationship between formulaic breast volume and risk of breast cancer based on linear measurements

10.21203/rs.3.rs-23397/v6 ◽

2020 ◽

Author(s):

Xiaoxia Li ◽

Chunlan Zhou ◽

Yanni Wu ◽

Xiaohong Chen

Keyword(s):

Breast Cancer ◽

Logistic Regression ◽

Propensity Score ◽

Propensity Score Matching ◽

Conditional Logistic Regression ◽

Control Group ◽

Case Group ◽

Breast Volume ◽

Linear Measurements ◽

Significant Difference

Abstract Background: Whether breast volume is a risk factor for breast cancer is controversial. This study aimed to evaluate whether a significant association between breast volume and risk of breast cancer, based on linear measurements,was present by applying propensity score matching (PSM).Methods: The study was designed as a hospital-based case-control study. Between March 2018 and May 2019, 208 cases and 340 controls were retrospectively reviewed. Information on menarche, smoking, feeding mode, oral contraceptives, reproductive history and family history was obtained through a structured questionnaire. Breast volume was calculated using a formula based on linear measurements of breast parameters. Cox regression and PSM were used to estimate odds ratios and 95% confidence intervals for breast cancer using risk factors adjusted for potential confounders.Results: There was a significant difference in breast volume between the two groups before propensity score matching(P = 0.014) . Binary logistic regression showed that the risk of breast cancer was slightly higher in the case group with larger breast volumes than in the control group（P = 0.009, OR = 1.002， 95%CI：1.000~1.003). However, there was no significant statistical difference between the two groups using an independent sample Mann-Whitney U test (P = 0.438) or conditional logistic regression (P = 0.446).Conclusions: After PSM for potential confounding factors, there is no significant difference in breast volume estimated by BREAST-V formula between the case group and the control group. The risk of breast cancer may not be related to breast volume in Chinese women.

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Relationship between formulaic breast volume and risk of breast cancer based on linear measurements

10.21203/rs.3.rs-23397/v5 ◽

2020 ◽

Author(s):

xiaoxia li ◽

Chunlan Zhou ◽

Yanni Wu ◽

Xiaohong Chen

Keyword(s):

Breast Cancer ◽

Logistic Regression ◽

Propensity Score ◽

Propensity Score Matching ◽

Conditional Logistic Regression ◽

Control Group ◽

Case Group ◽

Breast Volume ◽

Linear Measurements ◽

Significant Difference

Abstract Background: Whether breast volume is a risk factor for breast cancer is controversial. This study aimed to evaluate whether a significant association between breast volume and risk of breast cancer, based on linear measurements,was present by applying propensity score matching (PSM).Methods: The study was designed as a hospital-based case-control study. Between March 2018 and May 2019, 208 cases and 340 controls were retrospectively reviewed. Information on menarche, smoking, feeding mode, oral contraceptives, reproductive history and family history was obtained through a structured questionnaire. Breast volume was calculated using a formula based on linear measurements of breast parameters. Cox regression and PSM were used to estimate odds ratios and 95% confidence intervals for breast cancer using risk factors adjusted for potential confounders. Results: There was a significant difference in breast volume between the two groups before propensity score matching(P = 0.014) . Binary logistic regression showed that the risk of breast cancer was slightly higher in the case group with larger breast volumes than in the control group（P = 0.009, OR = 1.002， 95%CI：1.000~1.003). However, there was no significant statistical difference between the two groups using an independent sample Mann-Whitney U test (P = 0.438) or conditional logistic regression (P = 0.446). Conclusions: After PSM for potential confounding factors, there is no significant difference in breast volume estimated by BREAST-V formula between the case group and the control group. The risk of breast cancer may not be related to breast volume in Chinese women.

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Relationship between formulaic breast volume and risk of breast cancer based on linear measurement

10.21203/rs.3.rs-23397/v3 ◽

2020 ◽

Author(s):

xiaoxia li ◽

Chunlan Zhou ◽

Yanni Wu ◽

Xiaohong Chen

Keyword(s):

Breast Cancer ◽

Logistic Regression ◽

Propensity Score ◽

Propensity Score Matching ◽

Cox Regression ◽

Conditional Logistic Regression ◽

Control Group ◽

Breast Volume ◽

Linear Measurements ◽

Significant Difference

Abstract Background: Whether breast volume is a risk factor for breast cancer is controversial. This study aimed to evaluate whether a significant association between breast volume and risk of breast cancer, based on linear measurements,was present by applying propensity score matching (PSM).Methods: The study was designed as a hospital-based case-control study. Between March 2018 and May 2019, 208 cases and 340 controls were retrospectively reviewed. Information on menarche, smoking, feeding mode, oral contraceptives, reproductive history and family history was obtained through a structured questionnaire. Breast volume was calculated using a formula based on linear measurements of breast parameters. Cox regression and PSM were used to estimate odds ratios and 95% confidence intervals for breast cancer using risk factors adjusted for potential confounders. Results: There was a significant difference in breast volume between the two groups before propensity score matching(P = 0.014) . Binary logistic regression showed that the risk of breast cancer was slightly higher in the case group with larger breast volumes than in the control group（P = 0.009, OR = 1.002， 95%CI：1.000~1.003). However, there was no significant statistical difference between the two groups using an independent sample Mann-Whitney U test (P = 0.438) or conditional logistic regression (P = 0.446). Conclusions: After PSM for potential confounding factors, the breast volume of cases did not differ from that of controls. The risk of breast cancer may not be related to breast volume in Chinese women.

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Relationship between formulaic breast volume and risk of breast cancer based on linear measurements

10.21203/rs.3.rs-23397/v2 ◽

2020 ◽

Author(s):

xiaoxia li ◽

Chunlan Zhou ◽

Yanni Wu ◽

Xiaohong Chen

Keyword(s):

Breast Cancer ◽

Logistic Regression ◽

Propensity Score ◽

Propensity Score Matching ◽

Cox Regression ◽

Conditional Logistic Regression ◽

Control Group ◽

Breast Volume ◽

Linear Measurements ◽

Significant Difference

Abstract Background: Whether breast volume is a risk factor for breast cancer is controversial. This study aimed to evaluate whether a significant association between breast volume and risk of breast cancer, based on linear measurements,was present by applying propensity score matching (PSM).Methods: The study was designed as a hospital-based case-control study. Between March 2018 and May 2019, 208 cases and 340 controls were retrospectively reviewed. Information on menarche, smoking, feeding mode, oral contraceptives, reproductive history and family history was obtained through a structured questionnaire. Breast volume was calculated using a formula based on linear measurements of breast parameters. Cox regression and PSM were used to estimate odds ratios and 95% confidence intervals for breast cancer using risk factors adjusted for potential confounders. Results: There was a significant difference in breast volume between the two groups before propensity score matching(P = 0.014) . Binary logistic regression showed that the risk of breast cancer was slightly higher in the case group with larger breast volumes than in the control group（P = 0.009, OR = 1.002， 95%CI：1.000~1.003). However, there was no significant statistical difference between the two groups using an independent sample Mann-Whitney U test (P = 0.438) or conditional logistic regression (P = 0.446). Conclusions: After PSM for potential confounding factors, the breast volume of cases did not differ from that of controls. The risk of breast cancer may not be related to breast volume in Chinese women.

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Relationship Between Formulaic Breast Volume And Risk Of Breast Cancer Based On Linear Measurement

10.21203/rs.3.rs-23397/v1 ◽

2020 ◽

Author(s):

xiaoxia li ◽

Chunlan Zhou ◽

Yanni Wu ◽

Xiaohong Chen

Keyword(s):

Breast Cancer ◽

Logistic Regression ◽

Propensity Score ◽

Propensity Score Matching ◽

Cox Regression ◽

Conditional Logistic Regression ◽

Linear Measurement ◽

Control Group ◽

Breast Volume ◽

Significant Difference

Abstract Background: Whether breast volume is a risk factor for breast cancer has been controversial. This study aimed to evaluate whether or not the significant association between breast volume and risk of breast cancer based on linear measurement by applying Propensity Score Matching (PSM) was present. Methods: The study was designed as a hospital-based case-control study. Between March 2018 and May 2019, 208 cases and 340 controls were retrospectively reviewed. Information on menarche, smoking, feeding mode, oral contraceptives, reproductive history and family history was obtained through a structured questionnaire. Calculate breast volume using formula based on the linear measurement of breast parameters. Cox regression and PSM were used to estimate odds ratios and 95% confidence intervals for breast cancer by risk factors adjusted for potential confounders. Results: There was a significant difference in breast volume between two groups before Propensity Score Matching(P=0.014) : P=0.009, OR=1.002, 95% CI: 1.000~1.003). Binary logistic regression showed that the risk of breast cancer was slightly higher in the case group with larger breast volume than in the control group（P=0.009, OR=1.002， 95%CI：1.000～1.003). However, there was no significant statistical difference between two groups in independent sample Mann-Whitney U test (P=0.438) and in conditional logistic regression (P=0.446). Conclusions: After PSM for the potential confounders factors, the breast volume of cases did not differ from that of controls. The risk of breast cancer may not related to breast volume in Chinese women.

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Faktor risiko obesitas pada ibu rumah tangga miskin

Jurnal Gizi Klinik Indonesia ◽

10.22146/ijcn.15361 ◽

2012 ◽

Vol 9 (1) ◽

pp. 1

Author(s):

Digna Niken Purwaningrum ◽

Hamam Hadi ◽

I Made Alit Gunawan

Keyword(s):

Physical Activity ◽

Risk Factors ◽

Logistic Regression ◽

Risk Factor ◽

Food Insecurity ◽

Energy Intake ◽

Conditional Logistic Regression ◽

Control Group ◽

Case Group ◽

Fat Intake

Background: Food insecurity is associated with allocation of income for high energy density food consumption that may cause obesity in poor family. In addition, low physical activity may lead to obesity, particularly in individual living in disadvantaged situation.Objective: To identify risk factors of obesity among poor housewives in Yogyakarta.Method: This was a case control study, case group was obese housewives and the control group was non obese housewives. The locations of the study were Bumijo and Pringgokusuman which have high population density. The samples were taken purposively. Each group consisted of 70 housewives (1:1) and were matched according to age. Mc.Nemar test and conditional logistic regression were used to identify the risk factors of obesity.Results: There was no difference in characteristics between the two groups. Food insecurity reached 91,43% in the control group, proportion of excessive energy intake reached 37.86% in the case group, higher than in control group (24.29%). Excessive fat intake in the case group reached 30% whereas in the control group was 28.57%. Low physical activity reached 40% in the case group, and 10% in the control group. The result of Mc.Nemar test showed that food insecurity, energy and fat intake had no significant association with obesity (p>0.05). While physical activity was associated with obesity (p=0.0001). The result of conditional logistic regression showed physical activity was dominant risk factor for obesity among poor housewives (R2=0.1916).Conclusion: Food security status was not a risk factor for obesity in poor families; energy intake and fat intake contributed to the prevalence of obesity though the influence was smaller than physical activity.

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Efficacy Evaluation of Thymosin Alpha 1 in Non-severe Patients With COVID-19: A Retrospective Cohort Study Based on Propensity Score Matching

Frontiers in Medicine ◽

10.3389/fmed.2021.664776 ◽

2021 ◽

Vol 8 ◽

Author(s):

ChenLu Huang ◽

Ling Fei ◽

Wei Xu ◽

WeiXia Li ◽

XuDong Xie ◽

...

Keyword(s):

Propensity Score ◽

Hospital Stay ◽

Propensity Score Matching ◽

Standard Therapy ◽

Control Group ◽

Thymosin Α1 ◽

Significant Difference ◽

Thymosin Alpha 1 ◽

And Control ◽

Related Mortality

Objective: Thymosin alpha 1 (Thymosin-α1) is a potential treatment for patients with COVID-19. We aimed to determine the effect of Thymosin-α1 in non-severe patients with COVID-19.Methods: We retrospectively enrolled 1,388 non-severe patients with COVID-19. The primary and secondary clinical outcomes were evaluated with comparisons between patients treated with or without Thymosin-α1 therapy.Results: Among 1,388 enrolled patients, 232 patients (16.7%) received both Thymosin-α1 therapy and standard therapy (Thymosin-α1 group), and 1,156 patients (83.3%) received standard therapy (control group). After propensity score matching (1:1 ratio), baseline characteristics were well-balanced between the Thymosin-α1 group and control group. The proportion of patients that progressed to severe COVID-19 is 2.17% for the Thymosin-α1 group and 2.71% for the control group (p = 0.736). The COVID-19-related mortality is 0.54% for the Thymosin-α1 group and 0 for the control group (p = 0.317). Compared with the control group, the Thymosin-α1 group had significantly shorter SARS-CoV-2 RNA shedding duration (13 vs. 16 days, p = 0.025) and hospital stay (14 vs. 18 days, p < 0.001). No statistically significant difference was found between the Thymosin-α1 group and control group in duration of symptoms (median, 4 vs. 3 days, p = 0.843) and antibiotic utilization rate (14.1% vs. 15.2%, p = 0.768).Conclusion: For non-severe patients with COVID-19, Thymosin-α1 can shorten viral RNA shedding duration and hospital stay but did not prevent COVID-19 progression and reduce COVID-19-related mortality rate.

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Serum and Saliva Levels of Cancer Antigen 15-3, Carcinoembryonic Antigen, Estradiol, Vaspin, and Obestatin as Biomarkers for the Diagnosis of Breast Cancer in Postmenopausal Women

Laboratory Medicine ◽

10.1093/labmed/lmaa013 ◽

2020 ◽

Vol 51 (6) ◽

pp. 620-627

Author(s):

Hyder Farahani ◽

Jamal Amri ◽

Mona Alaee ◽

Fathollah Mohaghegh ◽

Mohammad Rafiee

Keyword(s):

Breast Cancer ◽

Carcinoembryonic Antigen ◽

Correlation Coefficients ◽

Control Group ◽

Case Group ◽

Cancer Antigen ◽

Healthy Women ◽

Significant Difference ◽

Serum Cea ◽

Control Study

Abstract Objective To find suitable biomarkers for diagnosis of Breast cancer in serum and saliva; also, to examine the correlation between salivary and serum concentrations of suitable biomarkers. Methods This case-control study included 30 women with breast cancer as a case group and 30 healthy women as a matched control group. Blood and saliva specimens were collected from all participants. We evaluated serum and salivary cancer antigen 15-3 (CA15-3), carcinoembryonic antigen (CEA), estradiol, vaspin, and obestatin concentrations. Mann-Whitney U testing and Spearman correlation coefficients were used for statistical analysis. Results Serum and salivary concentrations of estradiol were significantly higher in patients with breast cancer (BC) than in healthy women (P < .05). Also, serum CEA and salivary obestatin concentrations were significantly higher in BC patients than in the control group (P < .05). However, there was no significant difference between other parameters in patients with BC and controls. We observed a positive correlation between serum and salivary concentrations of CA15-3, as well as a negative correlation between serum and salivary concentrations of vaspin and obestatin. Conclusion The results of this study demonstrated that concentrations of CEA and estradiol in serum, obestatin in serum and saliva, and estradiol in saliva were significantly different between the 2 groups.

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Therapeutic Impact of Initial Treatment for Chlamydia trachomatis Among Patients With Pelvic Inflammatory Disease: A Retrospective Cohort Study Using a National Inpatient Database in Japan

Clinical Infectious Diseases ◽

10.1093/cid/ciy862 ◽

2018 ◽

Vol 69 (2) ◽

pp. 316-322

Author(s):

Daisuke Shigemi ◽

Hiroki Matsui ◽

Kiyohide Fushimi ◽

Hideo Yasunaga

Keyword(s):

Chlamydia Trachomatis ◽

Propensity Score ◽

Pelvic Inflammatory Disease ◽

Propensity Score Matching ◽

Inflammatory Disease ◽

Initial Treatment ◽

Primary Outcome ◽

Control Group ◽

Short Term ◽

Significant Difference

Abstract Background Pelvic inflammatory disease (PID) is common among women of reproductive age and can be complicated by tuboovarian abscess (TOA), which is a serious and potentially life-threatening disease. However, recent mortality rates from PID on hospital admission and the short-term therapeutic usefulness of initial treatment for Chlamydia trachomatis remain unknown. Methods Using the Diagnosis Procedure Combination database, we identified patients who were diagnosed with PID on admission from July 2010 to March 2016 in Japan. We excluded patients who were pregnant, had cancer, or had missing data. Propensity score–adjusted analyses were performed to compare short-term outcomes between patients administered initial treatment for C. trachomatis and those without this treatment. The primary outcome was surgical intervention (laparotomy, laparoscopic surgery, and/or drainage procedure) during hospitalization. Results In total, 27841 eligible patients were identified. Of these patients, 2463 (8.8%) had TOA on admission. Mortality during hospitalization was 0.56% and 0.28% in the groups without and with TOA, respectively. Propensity score matching created 6149 pairs. A significant difference was observed in the primary outcome between those receiving initial treatment for C. trachomatis and the control group after propensity score matching (11.5% vs 13.4%; risk difference, −1.9%; 95% confidence interval, −3.1 to −0.7). The group that received initial treatment for C. trachomatis also had a significantly lower mortality rate. Conclusions In this retrospective nationwide study, initial treatment for C. trachomatis among hospitalized patients diagnosed with PID had clinical benefits in terms of improved short-term outcomes.

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