The Use of A Combined Clinical Symptom and Biomarker-Based Model to Predict Risk of Developing Reproductive Conditions and Fertility Potential.

成功怀孕需要排卵和月经周期、生活方式因素和稳定的激素水平的复杂计算。一个健康的生殖周期依赖于所有这些变量的精确同步。然而，在近30%的女性中，这些因素的协调存在不同程度的不稳定性，这可能导致她们的生殖周期中断，并导致随后的不孕。许多关于怀孕的多因素变量的数据，主要来自于对临床诊断为低生育能力人群的小规模研究。因此，缺乏来自尚未尝试受孕或表现出非典型症状的女性的可用数据。这些症状通常与其他常见疾病（如月经过多、肠易激综合征或间质性膀胱炎）的症状重叠，使得初级保健的鉴别诊断具有挑战性。此外，目前的NICE初级保健常规妇科评估指南限制了实验室测试和女性激素测试（生物标志物），并且由于目前的诊断框架，诊断往往延迟，平均在最初出现症状后6- 12年。一份由患者完成的、基于症状的护理问卷，旨在让女性自我识别自己的症状，并结合更全面的生物标志物小组，可以促进患者和医生之间的初步讨论，有可能减少诊断延误并鼓励早期治疗。这一研究方案的目的是开发一种临床预测模型，该模型基于患者自我识别的症状以及生物特征信息（激素、生殖和病史）。通过将这一模型应用于更广泛的人群，我们希望每个妇女自己的症状和生物学特征可以用来表明她的生育能力和生殖健康面临的潜在风险。

Achieving a successful pregnancy requires a complex calculus of ovulation and menstrual cycles, lifestyle factors and stable hormone levels. A healthy reproductive cycle is reliant on precise synchronisation of all these variables. However, in almost 30% of all women, there is some varying degree of instability in the harmonisation of these factors that can cause a disruption to their reproductive cycle and lead to subsequent infertility.Much of the data concerning the multifactorial variables involved in pregnancy, has predominantly been generated from small scale studies on a clinically diagnosed subfertile population. Consequently, there is a paucity of data available from females who are yet to attempt conception or who present with atypical symptomology.These symptoms often overlap with those of other common conditions (e.g., heavy periods, irritable bowel syndrome or interstitial cystitis), making a differential diagnosis challenging in primary care. Moreover, current NICE guidelines for routine gynaecological evaluation in primary care limits laboratory tests and female hormone testing (biomarkers) and as a consequence of the current diagnostic framework diagnosis is often delayed, on average 6--12 years after initially presenting with symptoms.A patient-completed, symptom-based care questionnaire designed to allow women to self-identify their own symptoms in combination with a more comprehensive biomarker panel could facilitate the initial discussions between patients and physicians, with the potential to reduce diagnostic delay and encourage earlier treatment.The aim of this program of research is to develop a model of clinical prediction, based on both patient self-identified symptoms together with biometric information (hormones, reproductive and medical history). By applying this model to the wider population, we hope that each woman's own symptoms and biology can be used to indicate the potential risk to her fertility and reproductive health.