{"title":"卵巢衰老与绝经时间模型研究。","authors":"Sean D Lawley, Nanette Santoro, Joshua Johnson","doi":"10.1007/s11538-025-01481-7","DOIUrl":null,"url":null,"abstract":"<p><p>Mathematical modeling of ovarian aging and menopause timing has a long history, dating back a half-century to the models of Nobel Prize winner Robert G. Edwards. More recently, such models have been used to investigate clinical interventions for women, which underscores the importance of scientific rigor in model development and analysis. In this paper, we analyze a recent model published in the biophysics literature. We first correct an error which invalidates claims about menopause age in different populations. We then use stochastic analysis to show how this model is a reparameterization of a prior model and put it in the framework of several prior models, which enables the application of extreme value theory. We prove some general extreme value theory results and use them to obtain detailed estimates of menopause age in this model. In particular, we derive a new expected menopause age formula which is orders of magnitude more accurate than the previous heuristic estimate. We further obtain rigorous analytical estimates of the full menopause age distribution and all its moments. We conclude by using these mathematical results to elucidate the physiological sources of menopause age variability.</p>","PeriodicalId":9372,"journal":{"name":"Bulletin of Mathematical Biology","volume":"87 8","pages":"104"},"PeriodicalIF":2.2000,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On Modeling Ovarian Aging and Menopause Timing.\",\"authors\":\"Sean D Lawley, Nanette Santoro, Joshua Johnson\",\"doi\":\"10.1007/s11538-025-01481-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Mathematical modeling of ovarian aging and menopause timing has a long history, dating back a half-century to the models of Nobel Prize winner Robert G. Edwards. More recently, such models have been used to investigate clinical interventions for women, which underscores the importance of scientific rigor in model development and analysis. In this paper, we analyze a recent model published in the biophysics literature. We first correct an error which invalidates claims about menopause age in different populations. We then use stochastic analysis to show how this model is a reparameterization of a prior model and put it in the framework of several prior models, which enables the application of extreme value theory. We prove some general extreme value theory results and use them to obtain detailed estimates of menopause age in this model. In particular, we derive a new expected menopause age formula which is orders of magnitude more accurate than the previous heuristic estimate. We further obtain rigorous analytical estimates of the full menopause age distribution and all its moments. We conclude by using these mathematical results to elucidate the physiological sources of menopause age variability.</p>\",\"PeriodicalId\":9372,\"journal\":{\"name\":\"Bulletin of Mathematical Biology\",\"volume\":\"87 8\",\"pages\":\"104\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2025-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Bulletin of Mathematical Biology\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1007/s11538-025-01481-7\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bulletin of Mathematical Biology","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s11538-025-01481-7","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
Mathematical modeling of ovarian aging and menopause timing has a long history, dating back a half-century to the models of Nobel Prize winner Robert G. Edwards. More recently, such models have been used to investigate clinical interventions for women, which underscores the importance of scientific rigor in model development and analysis. In this paper, we analyze a recent model published in the biophysics literature. We first correct an error which invalidates claims about menopause age in different populations. We then use stochastic analysis to show how this model is a reparameterization of a prior model and put it in the framework of several prior models, which enables the application of extreme value theory. We prove some general extreme value theory results and use them to obtain detailed estimates of menopause age in this model. In particular, we derive a new expected menopause age formula which is orders of magnitude more accurate than the previous heuristic estimate. We further obtain rigorous analytical estimates of the full menopause age distribution and all its moments. We conclude by using these mathematical results to elucidate the physiological sources of menopause age variability.
期刊介绍:
The Bulletin of Mathematical Biology, the official journal of the Society for Mathematical Biology, disseminates original research findings and other information relevant to the interface of biology and the mathematical sciences. Contributions should have relevance to both fields. In order to accommodate the broad scope of new developments, the journal accepts a variety of contributions, including:
Original research articles focused on new biological insights gained with the help of tools from the mathematical sciences or new mathematical tools and methods with demonstrated applicability to biological investigations
Research in mathematical biology education
Reviews
Commentaries
Perspectives, and contributions that discuss issues important to the profession
All contributions are peer-reviewed.