Search

Background: Clinical risk prediction tools for gestational diabetes (GDM) may be enhanced by measuring biomarkers in early pregnancy. Aim: To evaluate a two‐step GDM risk prediction tool incorporating fasting glucose (FG) and serum biomarkers in early pregnancy. Materials and methods: High molecular weight (HMW) adiponectin, omentin‐1 and interleukin‐6 (IL‐6) were measured at 12–15 weeks gestation in women with high risk of GDM from a randomised trial using a clinical risk prediction tool. GDM diagnosis (24–28 weeks) was evaluated using 1998 Australian Diabetes in Pregnancy (ADIPS) criteria and newer International Association of the Diabetes and Pregnancy Study Groups (IADPSG) criteria. Associations between biomarkers and development of GDM were examined using multivariable regression analysis. Area under the receiver‐operator curve (AUC), sensitivity and specificity were calculated to determine classification ability of each model compared to FG and maternal characteristics. Results: HMW adiponectin improved prediction of ADIPS GDM (AUC 0.85, sensitivity 50%, specificity 96.2%, P = 0.04), compared to FG and maternal factors (0.78, 35% and, 98.1%, respectively). HMW adiponectin <1.53 μg/mL further improved the model (AUC 0.87, sensitivity 75%, specificity 88.2%, P = 0.01). HMW adiponectin did not improve prediction of IADPSG GDM (AUC 0.84, sensitivity 64%, specificity 97.9%, P = 0.22) compared to FG and maternal factors (0.79, 56%, 93.8%). Omentin‐1 and IL‐6 did not significantly improve classification ability for GDM. Conclusions: A two‐step approach combining FG and HMW adiponectin to a validated clinical risk prediction tool improved sensitivity and predictive ability for ADIPS GDM. Further research is required to enhance GDM prediction using IADPSG criteria for application in clinical practice. [ABSTRACT FROM AUTHOR]

Summary: Objective: Polycystic ovary syndrome (PCOS) is associated with increased obesity with a greater propensity to weight gain and a lack of sustainable lifestyle interventions. Altered brown adipose tissue (BAT) thermogenesis is a potential contributor to obesity in PCOS. BAT activity and modulation have not been studied in PCOS. This observational study explored BAT thermogenesis and its associations in women with and without PCOS. Participants and methods: Cutaneous temperature was recorded from supraclavicular (indicator of BAT activity) and upper arm regions using dataloggers (SubCue, Calgary, Canada) in a cross‐sectional substudy, nested within a randomized control trial, of community‐recruited premenopausal women with (n = 47, Rotterdam diagnostic criteria) and without (n = 11) PCOS. Results: Complete temperature data were available in 44 PCOS (mean age: 30.0 ± 6.2, mean BMI: 29.3 ± 5.5) and 11 non‐PCOS (mean age: 33.0 ± 7.0, mean BMI: 25 ± 3) women. Women with PCOS had lower supraclavicular skin temperature compared to controls overall (33.9 ± 0.7 vs 34.5 ± 1, P < 0.05) and during sleep (34.5 ± 0.6 vs 35.2 ± 0.9, P < 0.001). In the PCOS group, supraclavicular skin temperature overall and over sleep and waking hours correlated inversely with testosterone (r = −0.41 P < 0.05, r = −0.485 P < 0.01 and r = −0.450 P < 0.01 respectively). Testosterone levels explained approximately 15%, 30% and 20% of the variability in supraclavicular skin temperature overall and over sleep and waking hours in women with PCOS, respectively. Conclusion: Women with PCOS have lower BAT activity compared to controls. BAT thermogenesis is negatively associated with androgen levels in PCOS. [ABSTRACT FROM AUTHOR]

background: Polycystic ovary syndrome (PCOS) is a common endocrine disorder with diverse reproductive and metabolic features. It is underpinned by insulin resistance that is exacerbated by obesity. Lifestyle modification is the first line treatment in PCOS, but it is associated with lowadherence and sustainability. In small studies, metformin improves outcomes such as hyperinsulinaemia, ovulation and menstrual cyclicity. We conducted a systematic review and meta-analysis to compare the effect of lifestyle modification + metformin with lifestyle modification+ placebo, and of metformin alone with lifestyle modification+placebo in PCOS on anthropometric, metabolic, reproductive and psychological outcomes. methods: Databases including MEDLINE, EMBASE, Pubmed, Scopus, Cochrane, PsycINFO, CINAHL, Clinical Trials registry and ANZCTR were searched for RCTs conducted on humans and published in English up to August 2014. Inclusion criteria were diagnosis of PCOS based on Rotterdam criteria (inclusive of National Institutes of Health criteria) at any age and with any BMI. Interventions of interest included lifestyle + metformin (with any dose and any duration) or metformin alone compared with lifestyle+placebo. results: Of 2372 identified studies, 12 RCTs were included for analysis comprising 608 women with PCOS. Lifestyle + metformin were associated with lowerBMI (mean difference (MD) 20.73 kg/m², 95%confidence intervals (CI) 21.14, 20.32, P = 0.0005) and subcutaneous adipose tissue (MD 292.49 cm², 95%CI 2164.14, 220.84, P = 0.01) and increased number of menstrual cycles (MD1.06, 95%CI 0.30, 1.82, P = 0.006) after 6 months compared with lifestyle+placebo. There were no differences in other anthropometric, metabolic (surrogate markers of insulin resistance, fasting and area under the curve glucose, lipids and blood pressure), reproductive (clinical and biochemical hyperandrogenism), and psychological (quality of life) outcomes after 6 months between lifestyle ° metformin compared with lifestyle+placebo. With metformin alone compared with lifestyle+placebo, weight and BMI were similar after 6 months, but testosterone was lower with metformin. conclusions: Lifestyle + metformin is associated with lower BMI and subcutaneous adipose tissue and improved menstruation in women with PCOS compared with lifestyle ° placebo over 6 months. Metformin alone compared with lifestyle showed similar BMI at 6 months. These results suggest the combination of lifestyle with metformin has a role to play in weight management: a key concern for women with PCOS. Existing study limitations include small sample sizes, short durations and risk of bias. With international guidelines now acknowledging that lifestyle and pharmacotherapy are required for weight loss and maintenance in obesity, future studies of appropriate size and duration are vital to clarify the role of metformin in PCOS management. [ABSTRACT FROM AUTHOR]

Objective: To compare total antimüllerian hormone (AMH), proAMH, AMHN,C, and the ratio of the two forms in predictive models for polycystic ovary syndrome (PCOS) diagnosis. Total AMH consists of proAMH (inactive precursor) and AMHN,C (receptor-competent), but neither isoform has been tested individually for their ability to predict PCOS diagnosis.Design: Cross-sectional study using biobanked samples collected between July 2008 and January 2010.Setting: Not applicable.Patient(s): Overweight, premenopausal women aged 18-45 years with PCOS (n = 45, with 21 fulfilling National Institutes of Health diagnostic criteria and 24 fulfilling European Society for Human Reproduction and Embryology/American Society for Reproductive Medicine (ESHRE) criteria, but not National Institutes of Health criteria) and without PCOS (n = 23 controls).Intervention(s): None.Main Outcome Measure(s): Serum concentrations of proAMH and total AMH (proAMH and AMHN,C combined) were determined by immunoassay. The AMHN,C concentrations were calculated by subtraction ([AMHN,C] = [total AMH] - [proAMH]). Relative levels of proAMH were expressed as the AMH prohormone index (API = [ProAMH]/[Total AMH] × 100).Result(s): In women with PCOS, total AMH, proAMH, and AMHN,C levels were higher, and the API was lower (P=.010), than in controls indicating increased conversion of proAMH to AMHN,C. Receiver-operating characteristic analysis for proAMH (area under the curve [AUC] = 0.82), AMHN,C (AUC = 0.86), and API (AUC = 0.70) did not improve the prediction for PCOS when compared with total AMH (AUC = 0.86).Conclusion(s): The proAMH and AMHN,C do not appear to improve the ability to predict a diagnosis of PCOS beyond total AMH assays. However, the ratio of inactive proAMH precursor to receptor-competent AMHN,C (API) differs in women with PCOS relative to unaffected controls indicating that AMH signaling mechanisms may be altered in women with PCOS. [ABSTRACT FROM AUTHOR]

Background: Clinical risk prediction tools for gestational diabetes (GDM) may be enhanced by measuring biomarkers in early pregnancy., Aim: To evaluate a two-step GDM risk prediction tool incorporating fasting glucose (FG) and serum biomarkers in early pregnancy., Materials and Methods: High molecular weight (HMW) adiponectin, omentin-1 and interleukin-6 (IL-6) were measured at 12-15 weeks gestation in women with high risk of GDM from a randomised trial using a clinical risk prediction tool. GDM diagnosis (24-28 weeks) was evaluated using 1998 Australian Diabetes in Pregnancy (ADIPS) criteria and newer International Association of the Diabetes and Pregnancy Study Groups (IADPSG) criteria. Associations between biomarkers and development of GDM were examined using multivariable regression analysis. Area under the receiver-operator curve (AUC), sensitivity and specificity were calculated to determine classification ability of each model compared to FG and maternal characteristics., Results: HMW adiponectin improved prediction of ADIPS GDM (AUC 0.85, sensitivity 50%, specificity 96.2%, P = 0.04), compared to FG and maternal factors (0.78, 35% and, 98.1%, respectively). HMW adiponectin <1.53 μg/mL further improved the model (AUC 0.87, sensitivity 75%, specificity 88.2%, P = 0.01). HMW adiponectin did not improve prediction of IADPSG GDM (AUC 0.84, sensitivity 64%, specificity 97.9%, P = 0.22) compared to FG and maternal factors (0.79, 56%, 93.8%). Omentin-1 and IL-6 did not significantly improve classification ability for GDM., Conclusions: A two-step approach combining FG and HMW adiponectin to a validated clinical risk prediction tool improved sensitivity and predictive ability for ADIPS GDM. Further research is required to enhance GDM prediction using IADPSG criteria for application in clinical practice., (© 2018 The Royal Australian and New Zealand College of Obstetricians and Gynaecologists.)

Introduction: As many as 30% of node-negative breast cancer patients relapse within five years, suggesting that current histological detection methods are inadequate for identifying metastatic disease. Detecting small number of cancer cells in the breast tissue or lymph node by reverse transcription-polymerase chain reaction (RT-PCR) assays using a combination of tissue and cancer specific markers might be very useful in the early detection or monitoring of the treatment. Mammaglobin is a member of the uteroglobin gene family and appears to be expressed only in breast tissue. Carcinoembryonic antigen has been the preferred molecular marker for detection of micro metastases in lymph nodes in almost all carcinomas., Materials and Methods: Samples were collected from randomly chosen breast cancer patients undergoing modified mastectomy or breast conserving surgery between September 2003 and July 2004. RT-PCR was applied to study the expression of MMG and CEA markers. Breast cancer micrometastases in axillary lymph nodes were also assessed., Results: The MMG marker was positive in 9/10 normal breast tissues, 3/3 breast fibroadenomas and 37/39 of breast carcinoma tissues, giving an overall sensitivity of 94%. The sensitivity was 80% for metastatic lymph node samples. On the other hand CEA showed 95% sensitivity for malignant breast tumors and 100% sensitivity for metastatic lymph nodes., Conclusions: RT-PCR using a combination of MMG and CEA markers is a powerful tool to complement current routine histopathology techniques for detection of breast cancer metastasis in axillary nodes.