Machine Learning and External Validation of the IDENTIFY Risk Calculator for Patients with Haematuria Referred to Secondary Care for Suspected Urinary Tract Cancer.

BACKGROUND: The IDENTIFY study developed a model to predict urinary tract cancer using patient characteristics from a large multicentre, international cohort of patients referred with haematuria. In addition to calculating an individual's cancer risk, it proposes thresholds to stratify them into very-low-risk (<1%), low-risk (1-<5%), intermediate-risk (5-<20%), and high-risk (≥20%) groups. OBJECTIVE: To externally validate the IDENTIFY haematuria risk calculator and compare traditional regression with machine learning algorithms. DESIGN, SETTING, AND PARTICIPANTS: Prospective data were collected on patients referred to secondary care with new haematuria. Data were collected for patient variables included in the IDENTIFY risk calculator, cancer outcome, and TNM staging. Machine learning methods were used to evaluate whether better models than those developed with traditional regression methods existed. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The area under the receiver operating characteristic curve (AUC) for the detection of urinary tract cancer, calibration coefficient, calibration in the large (CITL), and Brier score were determined. RESULTS AND LIMITATIONS: There were 3582 patients in the validation cohort. The development and validation cohorts were well matched. The AUC of the IDENTIFY risk calculator on the validation cohort was 0.78. This improved to 0.80 on a subanalysis of urothelial cancer prevalent countries alone, with a calibration slope of 1.04, CITL of 0.24, and Brier score of 0.14. The best machine learning model was Random Forest, which achieved an AUC of 0.76 on the validation cohort. There were no cancers stratified to the very-low-risk group in the validation cohort. Most cancers were stratified to the intermediate- and high-risk groups, with more aggressive cancers in higher-risk groups. CONCLUSIONS: The IDENTIFY risk calculator performed well at predicting cancer in patients referred with haematuria on external validation. This tool can be used by urologists to better counsel patients on their cancer risks, to prioritise diagnostic resources on appropriate patients, and to avoid unnecessary invasive procedures in those with a very low risk of cancer. PATIENT SUMMARY: We previously developed a calculator that predicts patients' risk of cancer when they have blood in their urine, based on their personal characteristics. We have validated this risk calculator, by testing it on a separate group of patients to ensure that it works as expected. Most patients found to have cancer tended to be in the higher-risk groups and had more aggressive types of cancer with a higher risk. This tool can be used by clinicians to fast-track high-risk patients based on the calculator and investigate them more thoroughly.

Assessing unknown potential-quality and limitations of different large language models in the field of otorhinolaryngology.

BACKGROUND: Large Language Models (LLMs) might offer a solution for the lack of trained health personnel, particularly in low- and middle-income countries. However, their strengths and weaknesses remain unclear. AIMS/OBJECTIVES: Here we benchmark different LLMs (Bard 2023.07.13, Claude 2, ChatGPT 4) against six consultants in otorhinolaryngology (ORL). MATERIAL AND METHODS: Case-based questions were extracted from literature and German state examinations. Answers from Bard 2023.07.13, Claude 2, ChatGPT 4, and six ORL consultants were rated blindly on a 6-point Likert-scale for medical adequacy, comprehensibility, coherence, and conciseness. Given answers were compared to validated answers and evaluated for hazards. A modified Turing test was performed and character counts were compared. RESULTS: LLMs answers ranked inferior to consultants in all categories. Yet, the difference between consultants and LLMs was marginal, with the clearest disparity in conciseness and the smallest in comprehensibility. Among LLMs Claude 2 was rated best in medical adequacy and conciseness. Consultants' answers matched the validated solution in 93% (228/246), ChatGPT 4 in 85% (35/41), Claude 2 in 78% (32/41), and Bard 2023.07.13 in 59% (24/41). Answers were rated as potentially hazardous in 10% (24/246) for ChatGPT 4, 14% (34/246) for Claude 2, 19% (46/264) for Bard 2023.07.13, and 6% (71/1230) for consultants. CONCLUSIONS AND SIGNIFICANCE: Despite consultants superior performance, LLMs show potential for clinical application in ORL. Future studies should assess their performance on larger scale.

Adversarial AI applied to cross-user inter-domain and intra-domain adaptation in human activity recognition using wireless signals.

In recent years, researchers have successfully recognised human activities using commercially available WiFi (Wireless Fidelity) devices. The channel state information (CSI) can be gathered at the access point with the help of a network interface controller (NIC card). These CSI streams are sensitive to human body motions and produce abrupt changes (fluctuations) in their magnitude and phase values when a moving object interacts with a transmitter and receiver pair. This sensing methodology is gaining popularity compared to traditional approaches involving wearable technology, as it is a contactless sensing strategy with no cumbersome sensing equipments fitted on the target with preserved privacy since no personal information of the subject is collected. In previous investigations, internal validation statistics have been promising. However, external validation results have been poor, due to model application to varying subjects with remarkably different environments. To address this problem, we propose an adversarial Artificial Intelligence AI model that learns and utilises domain-invariant features. We analyse model results in terms of suitability for inter-domain and intra-domain alignment techniques, to identify which is better at robustly matching the source to target domain, and hence improve recognition accuracy in cross-user conditions for HAR using wireless signals. We evaluate our model performance on different target training data percentages to assess model reliability on data scarcity. After extensive evaluation, our architecture shows improved predictive performance across target training data proportions when compared to a non-adversarial model for nine cross-user conditions with comparatively less simulation time. We conclude that inter-domain alignment is preferable for HAR applications using wireless signals, and confirm that the dataset used is suitable for investigations of this type. Our architecture can form the basis of future studies using other datasets and/or investigating combined cross-environmental and cross-user features.

The prospect of artificial intelligence to personalize assisted reproductive technology.

Infertility affects 1-in-6 couples, with repeated intensive cycles of assisted reproductive technology (ART) required by many to achieve a desired live birth. In ART, typically, clinicians and laboratory staff consider patient characteristics, previous treatment responses, and ongoing monitoring to determine treatment decisions. However, the reproducibility, weighting, and interpretation of these characteristics are contentious, and highly operator-dependent, resulting in considerable reliance on clinical experience. Artificial intelligence (AI) is ideally suited to handle, process, and analyze large, dynamic, temporal datasets with multiple intermediary outcomes that are generated during an ART cycle. Here, we review how AI has demonstrated potential for optimization and personalization of key steps in a reproducible manner, including: drug selection and dosing, cycle monitoring, induction of oocyte maturation, and selection of the most competent gametes and embryos, to improve the overall efficacy and safety of ART.

Mini-AFTERc: a controlled pilot trial of a nurse-led psychological intervention for fear of breast cancer recurrence.

OBJECTIVES: To determine the feasibility and acceptability of implementing the Mini-AFTERc intervention. DESIGN: Non-randomised cluster-controlled pilot trial. SETTING: Four NHS out-patient breast cancer centres in Scotland. PARTICIPANTS: Ninety-two women who had successfully completed primary treatment for breast cancer were screened for moderate levels of fear of cancer recurrence (FCR). Forty-five were eligible (17 intervention and 28 control) and 34 completed 3-month follow-up (15 intervention and 21 control). INTERVENTION: Mini-AFTERc, a single brief (30 min) structured telephone discussion with a specialist breast cancer nurse (SBCN) trained to target the antecedents of FCR. OUTCOMES: Feasibility and acceptability of Mini-AFTERc and the study design were assessed via recruitment, consent, retention rates, patient outcomes (measured at baseline, 2, 4, and 12 weeks), and post-study interviews with participants and SBCNs, which were guided by Normalisation Process Theory. RESULTS: Mini-AFTERc was acceptable to patients and SBCNs. SBCNs believe the implementation of Mini-AFTERc to be feasible and an extension of discussions that already happen routinely. SBCNs believe delivery, however, at the scale required would be challenging given current competing demands for their time. Recruitment was impacted by variability in the follow-up practices of cancer centres and COVID-19 lockdown. Consent and follow-up procedures worked well, and retention rates were high. CONCLUSIONS: The study provided invaluable information about the potential challenges and solutions for testing the Mini-AFTERc intervention more widely where limiting high FCR levels is an important goal following recovery from primary breast cancer treatment. TRIAL REGISTRATION: ClinicalTrials.gov, NCT0376382 . Registered on 4 December 2018.

ChatGPT Versus Consultants: Blinded Evaluation on Answering Otorhinolaryngology Case-Based Questions.

BACKGROUND: Large language models (LLMs), such as ChatGPT (Open AI), are increasingly used in medicine and supplement standard search engines as information sources. This leads to more "consultations" of LLMs about personal medical symptoms. OBJECTIVE: This study aims to evaluate ChatGPT's performance in answering clinical case-based questions in otorhinolaryngology (ORL) in comparison to ORL consultants' answers. METHODS: We used 41 case-based questions from established ORL study books and past German state examinations for doctors. The questions were answered by both ORL consultants and ChatGPT 3. ORL consultants rated all responses, except their own, on medical adequacy, conciseness, coherence, and comprehensibility using a 6-point Likert scale. They also identified (in a blinded setting) if the answer was created by an ORL consultant or ChatGPT. Additionally, the character count was compared. Due to the rapidly evolving pace of technology, a comparison between responses generated by ChatGPT 3 and ChatGPT 4 was included to give an insight into the evolving potential of LLMs. RESULTS: Ratings in all categories were significantly higher for ORL consultants (P<.001). Although inferior to the scores of the ORL consultants, ChatGPT's scores were relatively higher in semantic categories (conciseness, coherence, and comprehensibility) compared to medical adequacy. ORL consultants identified ChatGPT as the source correctly in 98.4% (121/123) of cases. ChatGPT's answers had a significantly higher character count compared to ORL consultants (P<.001). Comparison between responses generated by ChatGPT 3 and ChatGPT 4 showed a slight improvement in medical accuracy as well as a better coherence of the answers provided. Contrarily, neither the conciseness (P=.06) nor the comprehensibility (P=.08) improved significantly despite the significant increase in the mean amount of characters by 52.5% (n= (1470-964)/964; P<.001). CONCLUSIONS: While ChatGPT provided longer answers to medical problems, medical adequacy and conciseness were significantly lower compared to ORL consultants' answers. LLMs have potential as augmentative tools for medical care, but their "consultation" for medical problems carries a high risk of misinformation as their high semantic quality may mask contextual deficits.

Long-term follow-up to assess criteria for ovarian tissue cryopreservation for fertility preservation in young women and girls with cancer.

STUDY QUESTION: Do the Edinburgh Selection Criteria correctly identify female cancer patients under the age of 18 who are at risk of premature ovarian insufficiency (POI) as candidates for ovarian tissue cryopreservation (OTC)? SUMMARY ANSWER: Patient assessment using these criteria accurately identifies those at risk of POI, who can be offered OTC and future transplantation as a means of fertility preservation. WHAT IS KNOWN ALREADY: Treatment for childhood cancer can have adverse consequences on future fertility; at the time of diagnosis, fertility risk assessment should be undertaken in order to identify patients to whom fertility preservation should be offered. The Edinburgh selection criteria, based on planned cancer treatment and patient health status, are utilized to identify those at high risk and therefore eligible for OTC. However, this procedure is not without risk and there are few data on the efficacy of the procedure in prepubertal patients. As such, long-term follow-up of reproductive outcomes is necessary, to ensure that OTC is being offered appropriately. STUDY DESIGN, SIZE, DURATION: Cohort study encompassing all females diagnosed with cancer under the age of 18 in South East Scotland, from 1 January 1996 to 30 April 2020. Patients were followed up for reproductive outcomes to assess for diagnosis of POI. PARTICIPANTS/MATERIALS, SETTING, METHODS: A total of 638 eligible patients were identified; patients under the age of 12 or deceased before the age of 12 were excluded from the study, leaving a study population of 431 patients. Electronic records were reviewed for reproductive function, assessed by current menstruation, pregnancy (in the absence of POI diagnosis), reproductive hormone measurements, pubertal progression, or diagnosis of POI. Patients on hormonal contraception (other than for treatment of POI or panhypopituitarism with no history of gonadatoxic treatment) were excluded from analysis (n = 9). Analysis on remaining 422 patients was carried out using the Kaplan-Meier methods, with POI as the defined event, and Cox proportional hazards model. MAIN RESULTS AND THE ROLE OF CHANCE: In the study population of 431 patients, median ages at diagnosis and analysis were 9.8 and 22.2 years, respectively. Reproductive outcomes were unavailable in 142 patients; the assumption was made that these patients did not have POI, but a subanalysis excluding these patients was also performed. Of the 422 patients aged >12 at analysis and not taking hormonal contraception, OTC was offered to 37 patients and successfully performed in 25 patients. Of the 37 patients offered OTC (one at time of relapse), nine (24.3%) developed POI. Of the 386 not offered OTC, 11 (2.9%) developed POI. The probability of developing POI was significantly higher in those offered OTC (hazard ratio [HR] 8.7 [95% CI 3.6-21]; P < 0.0001), even when those patients with unknown outcomes were excluded from the analysis (HR 8.1 [95% CI 3.4-20]; P < 0.001). All patients offered OTC who developed POI did so after treatment for primary disease; in those not offered OTC, five patients (45.5%) developed POI after treatment for disease relapse. LIMITATIONS, REASONS FOR CAUTION: A significant number of patients had unknown reproductive outcomes; many of these patients were engaged in ongoing follow-up but did not have documented reproductive assessment. This may have introduced bias to the analysis and highlights the need for reproductive follow-up as part of routine cancer aftercare. In addition, the relatively young age of the patient population and short duration of follow-up in some cases demonstrates the need for ongoing follow-up of this cohort. WIDER IMPLICATIONS OF THE FINDINGS: The prevalence of POI after childhood cancer is low, but the Edinburgh selection criteria remain a robust tool for selecting those at high risk at the time of diagnosis, to offer OTC appropriately. However, disease relapse necessitating more intensive treatments remains a challenge. This study additionally highlights the importance of routine assessment and documentation of reproductive status in haematology/oncology follow-up. STUDY FUNDING/COMPETING INTEREST(S): K.D. is supported by a CRUK grant (C157/A25193). This work was undertaken in part in the MRC Centre for Reproductive Health, (supported by MRC grant MR/N022556/1). R.A.A. has received consulting fees from Ferring and Roche Diagnostics; payment from Merck and IBSA for educational events; and laboratory materials from Roche Diagnostics. The other authors have no competing interests to declare. TRIAL REGISTRATION NUMBER: N/A.

Models and Biomarkers for Ovarian Ageing.

The human ovarian reserve is defined by the number of non-growing follicles (NGFs) in the ovary, with the age-related decline in NGF population determining age at menopause for healthy women. In this chapter, the concept of ovarian reserve is explored in detail, with a sequence of models described that in principle allow any individual to be compared to the general population. As there is no current technology that can count the NGFs in a living ovary, we move our focus to biomarkers for the ovarian reserve. Using serum analysis and ultrasound it is possible to measure anti-Müllerian hormone (AMH), follicle-stimulating hormone (FSH), and ovarian volume (OV) and to count numbers of antral follicles (AFC). These are compared, with ovarian volume being the closest to a true biomarker for a wide range of ages and with AMH and AFC being the most popular for post-pubertal and pre-menopausal ages. The study of genetic and subcellular biomarkers for the ovarian reserve has produced less concrete results. Recent advances are described and compared in terms of limitations and potential. The chapter concludes with an overview of the future study indicated by our current knowledge and by current controversy in the field.

Spatio-temporal remodelling of the composition and architecture of the human ovarian cortical extracellular matrix during in vitro culture.

STUDY QUESTION: How does in vitro culture alter the human ovarian cortical extracellular matrix (ECM) network structure? SUMMARY ANSWER: The ECM composition and architecture vary in the different layers of the ovarian cortex and are remodelled during in vitro culture. WHAT IS KNOWN ALREADY: The ovarian ECM is the scaffold within which follicles and stromal cells are organized. Its composition and structural properties constantly evolve to accommodate follicle development and expansion. Tissue preparation for culture of primordial follicles within the native ECM involves mechanical loosening; this induces undefined modifications in the ECM network and alters cell-cell contact, leading to spontaneous follicle activation. STUDY DESIGN, SIZE, DURATION: Fresh ovarian cortical biopsies were obtained from six women aged 28-38 years (mean ± SD: 32.7 ± 4.1 years) at elective caesarean section. Biopsies were cut into fragments of ∼4 × 1 × 1 mm and cultured for 0, 2, 4, or 6 days (D). PARTICIPANTS/MATERIALS, SETTING, METHODS: Primordial follicle activation, stromal cell density, and ECM-related protein (collagen, elastin, fibronectin, laminin) positive area in the entire cortex were quantified at each time point using histological and immunohistological analysis. Collagen and elastin content, collagen fibre characteristics, and follicle distribution within the tissue were further quantified within each layer of the human ovarian cortex, namely the outer cortex, the mid-cortex, and the cortex-medulla junction regions. MAIN RESULTS AND THE ROLE OF CHANCE: Primordial follicle activation occurred concomitantly with a loosening of the ovarian cortex during culture, characterized by an early decrease in stromal cell density from 3.6 ± 0.2 × 106 at day 0 (D0) to 2.8 ± 0.1 × 106 cells/mm3 at D2 (P = 0.033) and a dynamic remodelling of the ECM. Notably, collagen content gradually fell from 55.5 ± 1.7% positive area at D0 to 42.3 ± 1.1% at D6 (P = 0.001), while elastin increased from 1.1 ± 0.2% at D0 to 1.9 ± 0.1% at D6 (P = 0.001). Fibronectin and laminin content remained stable. Moreover, collagen and elastin distribution were uneven throughout the cortex and during culture. Analysis at the sub-region level showed that collagen deposition was maximal in the outer cortex and the lowest in the mid-cortex (69.4 ± 1.2% versus 53.8 ± 0.8% positive area, respectively, P < 0.0001), and cortical collagen staining overall decreased from D0 to D2 (65.2 ± 2.4% versus 60.6 ± 1.8%, P = 0.033) then stabilized. Elastin showed the converse distribution, being most concentrated at the cortex-medulla junction (3.7 ± 0.6% versus 0.9 ± 0.2% in the outer cortex, P < 0.0001), and cortical elastin peaked at D6 compared to D0 (3.1 ± 0.5% versus 1.3 ± 0.2%, P < 0.0001). This was corroborated by a specific signature of the collagen fibre type across the cortex, indicating a distinct phenotype of the ovarian cortical ECM depending on region and culture period that might be responsible for the spatio-temporal and developmental pattern of follicular distribution observed within the cortex. LARGE SCALE DATA: N/A. LIMITATIONS, REASONS FOR CAUTION: Ovarian cortical biopsies were obtained from women undergoing caesarean sections. As such, the data obtained may not accurately reflect the ECM distribution and structure of non-pregnant women. WIDER IMPLICATIONS OF THE FINDINGS: Clarifying the composition and architecture signature of the human ovarian cortical ECM provides a foundation for further exploration of ovarian microenvironments. It is also critical for understanding the ECM-follicle interactions regulating follicle quiescence and awakening, leading to improvements in both in vitro activation and in vitro growth techniques. STUDY FUNDING/COMPETING INTEREST(S): Medical Research Council grant MR/R003246/1 and Wellcome Trust Collaborative Award in Science: 215625/Z/19/Z. The authors have no conflicts to declare. TRIAL REGISTRATION NUMBER: N/A.

Survival after breast cancer in women with a subsequent live birth: Influence of age at diagnosis and interval to subsequent pregnancy.

BACKGROUND: There remains a considerable concern among both patients and oncologists that having a live birth (LB) after breast cancer might adversely impact survival. METHODS: analysis of survival in a national cohort of women with breast cancer diagnosed at age 20-39 years between 1981 and 2017 (n = 5181), and subsequent LB using Scottish Cancer Registry and national maternity records. Cases had at least one subsequent LB, each was matched with up to six unexposed cases without subsequent LB, accounting for guaranteed time bias. RESULTS: In 290 women with a LB after diagnosis, overall survival was increased compared to those who did not have a subsequent LB, HR 0.65 (95%CI 0.50-0.85). Women with subsequent LB who had not had a pregnancy before breast cancer showed increased survival (HR 0.56, 0.38-0.82). There was a progressively greater interaction of subsequent LB with survival with younger age, thus for women aged 20-25 years, HR 0.30 (0.12-0.74) vs. those aged 36-39, HR 0.89 (0.42-1.87). In women with LB within five years of diagnosis, survival was also increased (HR 0.66; 0.49-0.89). Survival following LB was similar to unexposed women by ER status (both positive and negative) and in those known to have been exposed to chemotherapy. CONCLUSIONS: This analysis provides further evidence that for the growing number of women who wish to have children after breast cancer, LB does not have a negative impact on overall survival. This finding was confirmed within subgroups, including the youngest women and those not previously pregnant.

Diagnostic and predictive accuracy of anti-mullerian hormone for ovarian function after chemotherapy in premenopausal women with early breast cancer.

PURPOSE: Accurate diagnosis and prediction of loss of ovarian function after chemotherapy for premenopausal women with early breast cancer (eBC) is important for future fertility and clinical decisions regarding the need for subsequent adjuvant ovarian suppression. We have investigated the value of anti-mullerian hormone (AMH) as serum biomarker for this. METHODS: AMH was measured in serial blood samples from 206 premenopausal women aged 40-45 years with eBC, before and at intervals after chemotherapy. The diagnostic accuracy of AMH for loss of ovarian function at 30 months after chemotherapy and the predictive value for that of AMH measurement at 6 months were analysed. RESULTS: Undetectable AMH showed a high diagnostic accuracy for absent ovarian function at 30 months with AUROC 0.89 (96% CI 0.84-0.94, P < 0.0001). PPV of undetectable AMH at 6 months for a menopausal estradiol level at 30 months was 0.77. In multivariate analysis age, pre-treatment AMH and FSH, and taxane treatment were significant predictors, and combined with AMH at 6 months, gave AUROC of 0.90 (95% CI 0.86-0.94), with PPV 0.79 for loss of ovarian function at 30 months. Validation by random forest models with 30% data retained gave similar results. CONCLUSIONS: AMH is a reliable diagnostic test for lack of ovarian function after chemotherapy in women aged 40-45 with eBC. Early analysis of AMH after chemotherapy allows identification of women who will not recover ovarian function with good accuracy. These analyses will help inform treatment decisions regarding adjuvant endocrine therapy in women who were premenopausal before starting chemotherapy.

Changes in Circulating Kisspeptin Levels During Each Trimester in Women With Antenatal Complications.

CONTEXT: Antenatal complications such as hypertensive disorders of pregnancy (HDP), fetal growth restriction (FGR), gestational diabetes (GDM), and preterm birth (PTB) are associated with placental dysfunction. Kisspeptin has emerged as a putative marker of placental function, but limited data exist describing circulating kisspeptin levels across all 3 trimesters in women with antenatal complications. OBJECTIVE: We aimed to assess whether kisspeptin levels are altered in women with antenatal complications. METHODS: Women with antenatal complications (n = 105) and those with uncomplicated pregnancies (n = 265) underwent serial ultrasound scans and blood sampling at the Early Pregnancy Assessment Unit at Hammersmith Hospital, UK, at least once during each trimester (March 2014 to March 2017). The women with antenatal complications (HDP [n = 32], FGR [n = 17], GDM [n = 35], PTB [n = 11], and multiple complications [n=10]) provided 373 blood samples and the controls provided 930 samples. Differences in circulating kisspeptin levels were assessed. RESULTS: Third-trimester kisspeptin levels were higher than controls in HDP but lower in FGR. The odds of HDP adjusted for gestational age, maternal age, ethnicity, BMI, smoking, and parity were increased by 30% (95% CI, 16%-47%; P < 0.0001), and of FGR were reduced by 28% (95% CI, 4-46%; P = 0.025), for every 1 nmol/L increase in plasma kisspeptin. Multiple of gestation-specific median values of kisspeptin were higher in pregnancies affected by PTB (P = 0.014) and lower in those with GDM (P = 0.020), but not significantly on multivariable analysis. CONCLUSION: We delineate changes in circulating kisspeptin levels at different trimesters and evaluate the potential of kisspeptin as a biomarker for antenatal complications.

Family size and duration of fertility in female cancer survivors: a population-based analysis.

OBJECTIVE: To assess family size and timescale for achieving pregnancy in women who remain fertile after cancer. DESIGN: Population-based analysis. SETTING: National databases. PATIENT(S): All women diagnosed with cancer before the age of 40 years in Scotland, 1981-2012 (n = 10,267) with no previous pregnancy; each was matched with 3 population controls. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): The number and timing of pregnancy and live birth after cancer diagnosis, to 2018. RESULT(S): In 10,267 cancer survivors, the hazard ratio for a subsequent live birth was 0.56 (95% confidence interval, 0.53-0.58) overall. In women who achieved a subsequent pregnancy, age at live birth increased (mean ± SD, 31.2 ± 5.5 vs. 29.7 ± 6.1 in controls), and the family size was lower (2.0 ± 0.8 vs. 2.3 ± 1.1 live births). These findings were consistent across several diagnoses. The interval from diagnosis to last pregnancy was similar to that of controls (10.7 ± 6.4 vs. 10.9 ± 7.3 years) or significantly increased, for example, after breast cancer (6.2 ± 2.8 vs. 5.3 ± 3.3 years) and Hodgkin lymphoma (11.1 ± 5.1 vs. 10.1 ± 5.8 years). CONCLUSION(S): These data quantify the reduced chance of live birth after cancer. Women who subsequently conceived achieved a smaller family size than matched controls, but the period of time after cancer diagnosis across which pregnancies occurred was similar or, indeed, increased. Thus, we did not find evidence that women who were able to achieve a pregnancy after cancer had a shorter timescale over which they have pregnancies.

Performance of plasma kisspeptin as a biomarker for miscarriage improves with gestational age during the first trimester.

OBJECTIVE: To compare the performance of kisspeptin and beta human chorionic gonadotropin (ßhCG), both alone and in combination, as biomarkers for miscarriage throughout the first trimester. DESIGN: Prospective, nested case-control study. SETTING: Tertiary Centre, Queen Charlotte Hospital, London, United Kingdom. PATIENT(S): Adult women who had miscarriages (n = 95, 173 samples) and women with healthy pregnancies (n = 265, 557 samples). INTERVENTION(S): The participants underwent serial ultrasound scans and blood sampling for measurement of plasma kisspeptin and ßhCG levels during the first trimester. MAIN OUTCOME MEASURE(S): The ability of plasma kisspeptin and ßhCG levels to distinguish pregnancies complicated by miscarriage from healthy pregnancies unaffected by miscarriage. RESULT(S): Gestation-adjusted levels of circulating kisspeptin and ßhCG were lower in samples from women with miscarriages than in women with healthy pregnancies by 79% and 70%, respectively. The area under the receiver-operating characteristic curve for identifying miscarriage during the first trimester was 0.874 (95% confidence interval [CI] 0.844-0.904) for kisspeptin, 0.859 (95% CI 0.820-0.899) for ßhCG, and 0.916 (95% CI 0.886-0.946) for the sum of the two markers. The performance of kisspeptin in identifying miscarriage improved with increasing length of gestation, whereas that of ßhCG worsened. A decision matrix incorporating kisspeptin, ßhCG, and gestational age had 83% to 87% accuracy for the prediction of miscarriage. CONCLUSION(S): Plasma kisspeptin is a promising biomarker for miscarriage and provides additional value to ßhCG alone, especially during later gestational weeks of the first trimester.

Clinical and biochemical discriminants between functional hypothalamic amenorrhoea (FHA) and polycystic ovary syndrome (PCOS).

BACKGROUND: Secondary oligo/amenorrhoea occurs in 3%-5% of women of reproductive age. The two most common causes are polycystic ovary syndrome (PCOS) (2%-13%) and functional hypothalamic amenorrhoea (FHA) (1%-2%). Whilst both conditions have distinct pathophysiology and their diagnosis is supported by guidelines, in practice, differentiating these two common causes of menstrual disturbance is challenging. Moreover, both diagnoses are qualified by the need to first exclude other causes of menstrual disturbance. AIM: To review clinical, biochemical and radiological parameters that could aid the clinician in distinguishing PCOS and FHA as a cause of menstrual disturbance. RESULTS: FHA is uncommon in women with BMI > 24 kg/m2 , whereas both PCOS and FHA can occur in women with lower BMIs. AMH levels are markedly elevated in PCOS; however, milder increases may also be observed in FHA. Likewise, polycystic ovarian morphology (PCOM) is more frequently observed in FHA than in healthy women. Features that are differentially altered between PCOS and FHA include LH, androgen, insulin, AMH and SHBG levels, endometrial thickness and cortisol response to CRH. Other promising diagnostic tests with the potential to distinguish these two conditions pending further study include assessment of 5-alpha-reductase activity, leptin, INSL3, kisspeptin and inhibin B levels. CONCLUSION: Further data directly comparing the discriminatory potential of these markers to differentiate PCOS and FHA in women with secondary amenorrhoea would be of value in defining an objective probability for PCOS or FHA diagnosis.

Endocrine Requirements for Oocyte Maturation Following hCG, GnRH Agonist, and Kisspeptin During IVF Treatment.

Objective: The maturation of oocytes to acquire competence for fertilization is critical to the success of in vitro fertilization (IVF) treatment. It requires LH-like exposure, provided by either human chorionic gonadotropin (hCG), or gonadotropin releasing hormone agonist (GnRHa). More recently, the hypothalamic stimulator, kisspeptin, was used to mature oocytes. Herein, we examine the relationship between the endocrine changes following these agents and oocyte maturation. Design: Retrospective cohort study. Methods: Prospectively collected hormonal data from 499 research IVF cycles triggered with either hCG, GnRHa, or kisspeptin were evaluated. Results: HCG-levels (121 iU/L) peaked at 24 h following hCG, whereas LH-levels peaked at ~4 h following GnRHa (140 iU/L), or kisspeptin (41 iU/L). HCG-levels were negatively associated with body-weight, whereas LH rises following GnRHa and kisspeptin were positively predicted by pre-trigger LH values. The odds of achieving the median mature oocyte yield for each trigger were increased by hCG/LH level. Progesterone rise during oocyte maturation occurred precipitously following each trigger and strongly predicted the number of mature oocytes retrieved. Progesterone rise was positively associated with the hCG-level following hCG trigger, but negatively with LH rise following all three triggers. The rise in progesterone per mature oocyte at 12 h was greater following GnRHa than following hCG or kisspeptin triggers. Conclusion: The endocrine response during oocyte maturation significantly differed by each trigger. Counter-intuitively, progesterone rise during oocyte maturation was negatively associated with LH rise, even when accounting for the number of mature oocytes retrieved. These data expand our understanding of the endocrine changes during oocyte maturation and inform the design of future precision-triggering protocols.

Pharmacodynamic Response to Anti-thyroid Drugs in Graves' Hyperthyroidism.

Objective: Graves' disease is the commonest cause of hyperthyroidism in populations with sufficient dietary iodine intake. Anti-thyroid drugs (ATD) are often used as the initial treatment for Graves' hyperthyroidism, however there is a paucity of data relating the dose of ATD therapy to the effect on thyroid hormone levels, increasing the risk of both over- and under-treatment. We aimed to determine the pharmacodynamic response to the ATD carbimazole. Design: Retrospective cohort study. Methods: Participants were patients (n = 441) diagnosed with Graves' disease at Imperial College Healthcare NHS Trust between 2009 and 2018. The main outcome measure was change in thyroid hormone levels in response to ATD. Results: Baseline thyroid hormone levels were positively associated with TSH receptor antibody titres (P < 0.0001). Baseline free triiodothyronine (fT3) were linearly related to free thyroxine (fT4) levels in the hyperthyroid state (fT3 = fT4*0.97-11), and fell proportionately with carbimazole. The percentage falls in fT4 and fT3 per day were associated with carbimazole dose (P < 0.0001). The magnitude of fall in thyroid hormones after the same dose of carbimazole was lower during follow up than at the initiation visit. The fall in thyroid hormone levels approximated to a linear response if assessed at least 3 weeks after commencement of carbimazole. Following withdrawal of antithyroid drug treatment, the risk of relapse was greater in patients with higher initial fT4, initial TSH receptor antibody titre, males, smokers, and British Caucasian ethnicity. Conclusion: We identify a dose-response relationship for fall in thyroid hormones in response to carbimazole to aid in the selection of dose for Graves' hyperthyroidism.

A controlled pilot trial of a nurse-led intervention (Mini-AFTERc) to manage fear of cancer recurrence in patients affected by breast cancer.

BACKGROUND: Fear of cancer recurrence (FCR) is common in people affected by breast cancer. FCR is associated with increased health service and medication use, anxiety, depression and reduced quality of life. Existing interventions for FCR are time and resource intensive, making implementation in a National Health Service (NHS) setting challenging. To effectively manage FCR in current clinical practice, less intensive FCR interventions are required. Mini-AFTERc is a structured 30-min counselling intervention delivered over the telephone and is designed to normalise moderate FCR levels by targeting unhelpful behaviours and misconceptions about cancer recurrence.This multi-centre non-randomised controlled pilot trial will investigate the feasibility of delivering the Mini-AFTERc intervention, its acceptability and usefulness, in relation to specialist breast cancer nurses (SBCNs) and patients. This protocol describes the rationale, methods and analysis plan for this pilot trial of the Mini-AFTERc intervention in everyday practice. METHODS: This study will run in four breast cancer centres in NHS Scotland, two intervention and two control centres. SBCNs at intervention centres will be trained to deliver the Mini-AFTERc intervention. Female patients who have completed primary breast cancer treatment in the previous 6 months will be screened for moderate FCR (FCR4 score: 10­14). Participants at intervention centres will receive the Mini-AFTERc intervention within 2 weeks of recruitment. SBCNs will audio record the intervention telephone discussions with participants. Fidelity of intervention implementation will be assessed from audio recordings. All participants will complete three separate follow-up questionnaires assessing changes in FCR, anxiety, depression and quality of life over 3 months. Normalisation process theory (NPT) will form the framework for semi-structured interviews with 20% of patients and all SBCNs. Interviews will explore participants' experience of the study, acceptability and usefulness of the intervention and factors influencing implementation within clinical practice. The ADePT process will be adopted to systematically problem solve and refine the trial design. DISCUSSION: Findings will provide evidence for the potential effectiveness, fidelity, acceptability and practicality of the Mini-AFTERc intervention, and will inform the design and development of a large randomised controlled trial (RCT). TRIAL REGISTRATION: ClinicalTrials.gov: NCT0376382. Registered 4th December 2018, https://clinicaltrials.gov/ct2/show/NCT03763825.