{"paper_id":"d4804673-f091-4c5d-8dfc-f33ce380f8e9","body_text":"Vol.:(0123456789)\nJournal of Assisted Reproduction and Genetics (2024) 41:1783–1791 \nhttps://doi.org/10.1007/s10815-024-03163-0\nASSISTED REPRODUCTION TECHNOLOGIES\nModelling and comparing the use of IVF and ICSI in Australia\nMaria Mazi1  · Georgina James1 · Peter Temple‑Smith1 · Ben W. J. Mol1\nReceived: 7 November 2023 / Accepted: 30 May 2024 / Published online: 24 June 2024 \n© The Author(s) 2024\nAbstract\nPurpose This study estimates the need of IVF/ICSI in Australia as compared to its actual uptake.\nMethods We created a model estimating for the annual demand for IVF/ICSI in a hypothetical infertile population, using \ndemographic data from medical literature and Australian government databases. For each category of infertility (tubal, \nsevere male, endometriosis, anovulation and unexplained), our estimated need for IVF/ICSI was compared to the actual \nIVF/ICSI uptake (ANZARD 2019). The model consisted of three categories depending on couples’ cause of infertility, i.e. \ncouples with absolute indications for IVF/ICSI (couples with severe male factor infertility and tubal obstruction); couples \nwith anovulatory infertility (couples with ovulation disorders) and couples with ovulatory infertility (couples suffering from \nunexplained infertility and endometriosis). The model was applied to each of these categories to determine the number of \ncouples that would require IVF/ICSI treatment after failing to conceive naturally or after following alternative treatment \nplans. The main outcomes of this study were the estimate of IVF/ICSI cycles and the difference between the estimate and \nthe reported number of IVF/ICSI cycles (2019 ANZARD report).\nResults We estimated that approximately 35,300 couples required IVF/ICSI treatment in Australia in 2019, while in 2019 \naccording to ANZARD, 46,000 couples underwent IVF/ICSI. A higher uptake of IVF/ICSI cycles than expected was spe-\ncifically reported in couples with unexplained infertility, ovulation disorders and endometriosis, while for tubal and severe \nmale infertility uptake seemed adequate.\nConclusion In Australia, there seems to be overservicing of IVF/ICSI, specifically for unexplained, ovulatory and endome-\ntriosis-related infertility.\nKeywords Infertility · Model population · Unexplained infertility · Fertility treatment · IVF · ICSI\nIntroduction\nIn vitro fertilisation (IVF) is the cornerstone of infertility \ntreatment, with Australia being one of the leading countries \nin the development of assisted reproductive technologies \n(IVF/ICSI) [1 ]. IVF was originally introduced in infertile \nwomen suffering from tubal pathology. Lesley Brown, the \nmother of world’s first IVF baby, Louise Brown, had her fal-\nlopian tubes removed just before her IVF treatment [2]. The \nintroduction of ICSI allowed treatment of couples suffering \nfrom severe male infertility [3]. After these initial successful \ncases, IVF was also introduced for longstanding infertility of \nother causes. An early randomised clinical trial confirmed \nthe effectiveness of IVF in women with unexplained infertil-\nity for 3 years or longer [4]. Since then, the use of IVF/ICSI \nhas gradually increased, with an exponential increase over \nthe last few decades for various reasons, including social \ncauses, such as later childbearing and an increase in the \nrange and availability of diagnostic tests [5]. Advancing age \nand ovarian ageing are the most common reasons why clini-\ncians urge women to undertake treatments to enhance and/\nor preserve their chances of having a baby in the future [6].\nDuring the last decade, infertility treatments have been \napplied to all types of infertility, including mild male fac-\ntor, anovulatory and unexplained infertility. This trend has \nresulted in a continuous increase in IVF treatments, also \nfor couples with a reasonable chance of natural conception \n[7]. It is important that IVF/ICSI treatment is applied where \nthere is sufficient medical need, and not treating those who \n * Maria Mazi \n mariamazis@gmail.com\n1 Education Program in Reproduction and Development, \nDepartment of Obstetrics and Gynaecology, School \nof Clinical Sciences at Monash Health, Monash University, \nClayton 3168, Australia\n\n1784 Journal of Assisted Reproduction and Genetics (2024) 41:1783–1791\ncan conceive with less invasive methods, thus avoiding \npotential harm as well as reducing cost of treatment.\nIt is important for patients with mild endometriosis and \nunexplained infertility or mild abnormalities not ruling out \nnatural conception to be completely informed by their physi-\ncians about their favourable chances for natural conception \nas well as alternative treatment options, (such as ovulatory \nhyperstimulation induction (OI) and intrauterine insemina-\ntion (IUI)), prior to IVF/ICSI treatment.\nRecent literature suggests that couples with unexplained \ninfertility have a better chance of becoming pregnant through \nnatural conception than couples with tubal obstruction or \nsevere male factor infertility [8]. Natural conception is also \npossible in women suffering from endometriosis if the sever-\nity of the disease is mild [8 ]. Moreover, couples suffering \nfrom unexplained infertility have a higher chance of sponta-\nneous conception than couples suffering from other causes \nof infertility [8]. It is important for these patients to be com-\npletely informed by their physicians about their favourable \nchance for natural conception as well as alternative treatment \noptions (such as ovulation induction (OI) and intrauterine \ninsemination (IUI)), prior to IVF/ICSI treatment.\nHere, our analysis we aim to explore the use of IVF/ICSI \nin Australia and to identify situations where more invasive \ntreatments, such as IVF/ICSI, could have been avoided. The \naim of the study was to develop a model that examines the \nuse of IVF/ICSI in Australia by comparing the estimated \ninfertile Australian population with the annual number of \nIVF/ICSI cycles reported.\nMaterials and methods\nOutline of the model\nA model-based approach was used to estimate the demand \nfor IVF/ICSI using data on medical infertility in Australia. \nEthics approval was not required for this study. The model \ncomprised of two main components: (i) an estimation of the \nnumber of infertile couples in Australia and (ii) an estimated \nbreakdown of infertility causes within the Australian popula-\ntion. These data provided an estimate of the number of cou-\nples annually that would require IVF/ICSI to treat infertility.\nData collection\nFor the demographic data collection, the total number of \nbirths (and stillbirths) was sourced from national databases \nand registries for 2019. The Australian and New Zealand \nAssisted Reproduction Database (ANZARD) was con-\nsulted for the number of IVF/ICSI cycles from 2019, as it \nwas the most recent year for which these data were avail-\nable. We considered the number of births assuming 16% \ninfertility rates to estimate the number of couples confronted \nwith infertility [9, 10] A literature search was conducted to \nidentify key variables between past models and this current \nmodel, and to determine the breakdown of infertility causes \naffecting the Australian population. Keywords including \nprevalence, infertility and the specific types of infertility \nindications were searched for the model. The studies were \nselected based on the similarity of the study population to \nthe Australian population (rebates for fertility treatment and \nsocioeconomic similarities). Variables used in the estimation \nof Australia’s annual number of infertile couples included \nthe following: infertility prevalence, recurrent miscarriage \nrate and number of births. We searched Google Scholar and \nPubMed to identify studies that provided factual data for \neach of these variables. Variables used in the estimation of \nIVF/ICSI demand included the following: prevalence of \nunilateral tubal obstruction, prevalence of bilateral tubal \nobstruction, prevalence of severe male factor, prevalence of \novulation disorders, prevalence of endometriosis and preva-\nlence of unexplained infertility (Table 1). Additionally, vari-\nables used in the breakdown of alternative treatment options \nincluded the following: ovulation induction with first-line \ntreatment (clomiphene citrate and letrozole), ovulation \ninduction with second-line treatment (gonadotropin therapy \nusing FSH/laparoscopic ovarian drilling (LOD)), the likeli-\nhood of natural conception based on Hunault’s prediction \nmodel, expectant management and identification of fertile \nwindow and, lastly, intrauterine insemination with controlled \novarian stimulation (IUI-COS) [17, 18].\nCauses of infertility\nOur model was developed using current evidence-based \ninfertility treatment data [15, 16, 19] and was designed to \ndetermine the need for IVF/ICSI in Australia. Using these \ndemographic data and the annual IVF/ICSI data for Aus -\ntralia in the 2019 ANZARD report [10], the model estimated \nthe number of infertile couples, based on a 16% infertility \nrate. A 16% infertility rate also aligns with the conclusions \nfrom live births in the 2019 ANZARD report [10] and the \ninfertility rate from a 2006 national fertility study [20]. For \nthe sensitivity analyses, we tested the model using two addi-\ntional infertility rates of 10% and 20%, based on studies by \nSnick et al. [16] and Jacobson [19].\nBased on the total infertile population that we estimated, \nthree different categories of infertility were defined:\n• Couples presenting with absolute indications for IVF/\nICSI (couples with unilateral and bilateral tubal obstruc-\ntion and/or severe male factor infertility)\n• Couples presenting with anovulatory infertility requiring \nIVF/ICSI\n\n1785Journal of Assisted Reproduction and Genetics (2024) 41:1783–1791 \n• Couples presenting with ovulatory infertility requiring \nIVF/ICSI\nA literature search was conducted to identify the prev -\nalence of the three categories within the total estimated \ninfertile population (16%). These prevalence figures were \nadded together to determine the total number of couples that \nrequire IVF/ICSI treatment (Fig.  1). This estimated number \nwas then compared to the reported number of couples had \nundergone IVF/ICSI in Australia in 2019.\nBased on the estimated number of couples, we calcu-\nlated the estimated number of cycles for each infertility \ncategory by multiplying the number of couples by 2, as \nANZARD data indicates that the average number of cycles \nundertaken by each couple in 2019 was 1.8 [10]. Our esti-\nmated number of cycles for each category was then com-\npared to the number of cycles of the infertility categories \nused by ANZARD for data collection [ 10]. The estimated \nnumber of cycles conducted for absolute indications was \ncompared to the sum of two equivalent ANZARD cat-\negories—tubal obstruction and severe male factor. The \nestimated number of cycles for ovulatory infertility was \ncompared to the reported cycle numbers for unexplained \ninfertility and endometriosis. The estimated number of \ncycles for anovulatory infertility was compared to the \nsum of the equivalent categories (ovulation disorders, \nother female factors, combination of female factors). In \nthe 2019 ANZARD report, “other female factors” includes \ninfertility caused by fibroids, ovulation disorders or pre-\nmature ovarian failure [10]. Our analysis did not include \ncalculations for patients with a combination of multiple \nfemale factors or with a combination of female and male \nfactors. Couples with unexplained infertility were also not \nincluded in this study. The calculations of this model were \nbased on the average age of first-time mothers in Australia \nin 2019, which was stated at 29.4 [21]. As the average age \nis below 35 years of age, for couples suffering from ovula-\ntory infertility, we assumed that the course of treatment \nwould follow the steps displayed on Fig.  1.\nResults\nEstimating the need for IVF/ICSI in Australia\nIn 2019, there was a total of 305,832 live births and out of \nthose, 15,158 were IVF/ICSI live births. The total infertile \npopulation in Australia in 2019 was calculated to be 40,766 \ncouples [10, 22, 23].\nTable  2 shows the breakdown of infertility causes and \nthe estimated number of cycles receiving IVF/ICSI (and \nnumber of cycles conducted) treatment of 16% infertility \nrate, excluding the number of couples with a combination \nof female and male causes. Comparison of the data from \nANZARD and the outputs of our model show an excess \nof IVF/ICSI treatments using each of the three different \ninfertility rates in couples suffering from both ovulatory and \nanovulatory infertility. The results also showed that fewer \ncycles were conducted for couples with absolute indications \nthan what it may be expected based on the results of our \nmodel (Table  2).\nTable 1  The breakdown of infertility causes after fertility workup and treatment success rate sourced from literature\nEstimating infertile population Prevalence (%) References\nMiscarriage rate (conditional on biochemical pregnancy) 20% (van der Steeg et al. [11]; Verhoeve et al. [12])\nPopulation infertility rate (reproductive age 15–44) 16% Kamphuis et al. [7]; Newman et al. [10]\nInfertility categories based on fertility workup\nUnilateral tubal obstruction 20% (Robert and Barbieri [13]; Tros et al. [14])\nBilateral tubal obstruction 4% (Robert and Barbieri [13]; Tros et al. [14])\nSevere male factor 15% (Robert and Barbieri [13])\nEndometriosis 5% Taylor [15]\nUnexplained infertility 30% Snick et al. [16]\nOvulation disorders 26% Snick et al. [16]\nTreatment options for couples with anovulatory infertility\n1st-line treatment success rates (CC/Let) 48% Falcone and Hurd [17]\n2nd-line treatment success rates (gonadotropin therapy/LOD) 32% Newman et al. [10]\nTreatment options for couples with ovulatory infertility\nSpontaneous pregnancy after 12 months (Hunault’s prediction values) 8% Snick et al. [16]\nExpectant management successful pregnancy rate 27% Gnoth et al. [18]\nIntrauterine insemination (IUI) successful pregnancy rate 50% Newman et al. [10]\n\n1786 Journal of Assisted Reproduction and Genetics (2024) 41:1783–1791\nANZARD indicates that 46,073 couples underwent IVF/\nICSI treatment in 2019 in Australia and the reported number \nof IVF/ICSI cycles was 84,081 in Australia and New Zealand. \nThe infertility rate was adjusted to 10% and 20% [15, 19] for \nthe sensitivity analysis (Tables 3 and 4 in the Appendix).\nSensitivity analyses\nFigure  2 shows a comparison between the estimated and \nthe reported treatment cycles for IVF/ICSI in Australia in \n2019 using the 16% infertility rate and for the 10% and 20% \ninfertility rates used in the sensitivity analysis.\nFig. 1  Identifying the infertile population based on national data and \ndetermining the need of IVF/ICSI according to a treatment model. \nFlowchart depicting the calculation process of the model. Initial step \nincluded the definition of infertile couples, i.e. couples that failed to \nachieve pregnancy after 12 months of regular, unprotected intercourse \nand couples that had two or more pregnancy losses. Infertile popu-\nlation was estimated based on the number of live births, IVF/ICSI \nlive births and number of still births within 1 calendar year. Infertile \npopulation was then divided into two categories: anovulatory and \novulatory infertility. Each category included an alternative treatment \nplan to achieve pregnancy. Couples that were not successful in falling \npregnant through the treatment plan were included in the total esti-\nmated number of couples that require IVF/ICSI to conceive. The esti-\nmate was then compared to the annual ART report [10]\n\n1787Journal of Assisted Reproduction and Genetics (2024) 41:1783–1791 \nDiscussion\nThis study developed a prognostic model that estimated \nthe demand for IVF and ICSI treatment in Australia. Prog-\nnostic models are used to help clinicians provide the best \npossible treatment option to infertile couples and to enable \nthe government to assess appropriate use of health funding \n[24]. While the demand for fertility treatment is clear for \ncouples with known infertility, (such as tubal obstruction \nand severe male factor infertility), it is often suggested that \ncouples suffering from anovulatory (ovulation disorders) \nor ovulatory infertility (mild endometriosis or unexplained \ninfertility) should explore alternative treatment options \nbefore proceeding to more advanced procedures such as \nIVF and/or ICSI.\nOur model showed an overuse of IVF/ICSI treatments \nin Australia when assuming a 10% or 16% infertility rate \nbut an underuse for an infertility rate of 20%. Moreover, the \nanalysis showed an overuse of IVF/ICSI cycles in couples \nsuffering from unexplained infertility, ovulation disorders \nand endometriosis. Possible explanations of this increased \nnumber of cycles in the unexplained infertility category may \nTable 2  Infertility category results and total estimated and reported infertile population in Australia in 2019 with 16% infertility rate\n*Our analysis estimated the total number of IVF/ICSI cycles in 2019, including both fresh and thawed cycles.**Other female factors include \ninfertility caused by fibroids, ovulation disorders or premature ovarian failure [10]. Our analysis did not account for combination of female fac-\ntors or a combination of male and female factors affecting fertility\nIndication for IVF/ICSI Estimated number \nof infertile couples\nEstimated needed num-\nber of IVF/ICSI cycles*\nPerformed number of IVF/ICSI cycles\nAbsolute indications Fresh Thawed Total\nTubal obstruction 16,727 33,454 1462 1188 2650\nSevere male factor 10,455 20,910 5539 3888 9427\nAnovulatory infertility\nOvulation disorders (**other female factors) 6408 12,816 13,092 7121 20,213\nCombination of female factors N/A N/A 4018 2833 6851\nCombination of male and female causes N/A N/A 3471 2533 6004\nOvulatory infertility\nEndometriosis 254 508 2634 1617 4251\nUnexplained infertility 1526 3052 8440 5828 14,268\nNot stated cause N/A N/A 12,797 7620 20,417\nTotal 35,370 70,740 51,453 32,628 84,081\nFig. 2  A comparison of the \ncombined estimated need of \nIVF/ICSI and the reported \nuse of IVF/ICSI in Australia \nin 2019 (including fresh and \nfrozen/thawed), according to \n10%, 16% and 20% infertility \nrate [10, 16, 19]\n41265\n70741\n92847\n940,18940,18940,18\n0\n10000\n20000\n30000\n40000\n50000\n60000\n70000\n80000\n90000\n100000\nytilitrefni%02ytilitrefni%61ytilitrefni%01\nThe use of IVF/ICSI cycles in Australia in 2019\nNumber of IVF/ICSI cycles estimated by model Number of performed IVF/ICSI cycle, published by ANZARD\n\n1788 Journal of Assisted Reproduction and Genetics (2024) 41:1783–1791\ninclude women of advanced maternal age accessing fertility \ntreatment or ovulatory disorders due to irregular periods as a \nsign of ageing. Additionally, the model showed that couples \nsuffering from tubal obstruction or severe male infertility are \nunder-treated as the performed number of IVF/ICSI cycles \nis lower than the estimated number of IVF/ICSI cycles. It is \ncommon that not all patients undergo complete laparoscopic \ntesting prior to accessing fertility treatment, leading to many \npatients suffering from tubal obstruction to be reported as \n“unexplained infertility”. Although it can be argued that this \noveruse is supported by a goal to provide couples with a \nfamily while reducing waiting time, careful consideration \nof the risks associated with IVF/ICSI procedures should be \ngiven when proceeding to treat couples with IVF/ICSI that \nhave a favourable prognosis for natural conception [25].\nResearch examining the benefits and harms associated \nwith infertility treatment has shown that the rise of IVF/\nICSI is driven by the focus of achieving a live birth (and \nsubsequently forming a family) while often overlooking its \npotential health and social impact on both the children and \nthe mother [1]. Despite the potential unknown issues, cou-\nples are often advised to continue their IVF/ICSI journey \neven though less advanced and alternative treatment options \ncan be made available for consideration before proceeding \nto IVF/ICSI. Our model was developed according to pre-\nvious prediction and prognostic models that highlight the \nimportance of natural conception and alternative treatments.\nPrognostic tools and national guidelines are available \nto guide physicians in deciding whether, and when, a cou-\nple will require IVF/ICSI or when they would benefit from \nwaiting and try alternative treatment options before opting \nfor more advanced IVF/ICSI treatments, if the woman is \nyounger than 35 years old. Research shows that prediction \nmodels can be clinically applied during fertility workup to \nprovide the couples with their best chances for a pregnancy \n[26]. Prognostic tools exist online and can be accessed by the \npublic; examples of prediction models include the YourFer-\ntilityTool from Fertility Coalition in Australia and the tool \nfrom the Dutch patient organisation Freya [27, 28]. These \nonline resources are readily available, easily to use and are \nimportant educational devices for patients to estimate their \nchance of spontaneous conception.\nAccessibility to IVF‑related medical rebates\nAlthough Australia has mostly private fertility clinics, IVF \ntreatment is more accessible than in other countries due to \nthe widely subsidised system. In the Netherlands, public \nfunding for fertility treatment includes an unlimited number \nof IUI cycles and three IVF or ICSI cycles [29]. Austral-\nians are eligible to claim rebates for their fertility treatment, \nvarying from $400 to $3200 from the government, through \nMedicare [30–32]. The model identified that the number of \nIVF/ICSI cycles is lower in the group of women suffering \nfrom tubal obstructions than the estimated number of cycles \ncalculated by the model. Several questions arise surround-\ning this finding, such as the accessibility of IVF/ICSI treat-\nment for these couples or the lack of specific gynaecological \ninvestigation prior to treatment. To understand this finding, \nmore holistic studies need to be conducted.\nLimitations of the model\nThe calculations in the model, even though this can be seen \nas a limitation, were developed using assumptions obtained \nfrom literature that provided similar trends across a variety \nof studies [10, 16, 19].\nMoreover, a limitation of the model is that it does not \ninclude infertility due to multifactorial causes. In most \nreports, the distribution of infertility causes includes the \ncombination of fertility complications, including combined \nmale and female factor infertility, a combination of male \nfactor and endometriosis as well as other combinations of \ncauses. Unfortunately, the ANZARD report does not include \na breakdown of the combination of infertility causes; thus, \nwe could not adjust this in our model. By including an esti-\nmate of the number of couples with a combination of causes \nfor infertility, the calculated number of couples, requiring \nIVF/ICSI treatment, would be lower than the numbers pre-\nsented in this project. A third limitation for this study is \nthat the ANZARD report is a collective of the data from \nAustralian and New Zealand IVF clinics that provides an \naggregate for the number of couples or women undergo-\ning IVF/ICSI treatment, as approximately 10% of the total \nnumber of cycles were conducted in New Zealand. Addition-\nally, the model does not include moderate male factor, where \nalternative therapies could be used to treat low sperm count. \nThere is potential for the model to be adjusted according to \ndata provided in future ANZARD reports to include same-\nsex couples and single mothers seeking fertility treatment as \nwell as mild forms of male infertility [10].\nThe purpose of this study was to examine the use of IVF \nand ICSI in Australia, in comparison to an estimated number \nof couples and cycles that require IVF/ICSI to treat infertility. \nTo improve clinical pathways that direct the use of IVF/ICSI, \nrestrictions to treatment and government funding policies for \nIVF/ICSI need to be revisited and restructured in order to pro-\nvide appropriate treatments for infertile couples in Australia.\nAppendix\nFor the number of total live deliveries, birth data included \ntotal number of births from single and multiple gestations. The \nannual number of pregnant women over 20 weeks of gestation, \n\n1789Journal of Assisted Reproduction and Genetics (2024) 41:1783–1791 \nnot attributable to IVF/ICSI births, from total deliveries, still-\nbirths and IVF/ICSI deliveries.\nTo identify the total number of non-IVF/ICSI l.\nFrom this, we calculated the fertile population, using 20% \nmiscarriage rate:\nNon − IVF∕ICSI pregnancies\n= number of total live deliveries − number of IVF∕ICSI deliveries\n+number of stillbirth\nWe then estimated the annual number of couples planning \npregnancy from our fertile population and the infertility rates \nused, to conduct a sensitivity analysis.\nFertile population = number of non − IVF∕\nICSIpregnancies divided by 1 − miscarriage rate\nPopulation planning pregnancy\n= ertile population divided by 1 − infertility rate.\nTable 3  Infertility category results and total estimated and reported infertile population in Australia in 2019 with 10% infertility rate\n*Our analysis estimated the total number of IVF/ICSI cycles in 2019, including both fresh and thawed cycles.**Other female factors include \ninfertility caused by fibroids, ovulation disorders or premature ovarian failure Newman et al. [10]. Our analysis did not account for combination \nof female factors or a combination of male and female factors affecting fertility\nIndication for IVF/ICSI Estimated number of \ninfertile couples\nEstimated needed number \nof IVF/ICSI cycles*\nPerformed number of IVF/ICSI \ncycles\nFresh Thawed Total\nTubal obstruction 9758 19,516 1462 1188 2650\nSevere male factor 6099 12,198 5539 3888 9427\nAnovulatory infertility\nOvulation disorders (**other female factors) 3738 7476 13,092 7121 20,213\nCombination of female factors N/A N/A 4018 2833 6851\nCombination of male and female causes N/A N/A 3471 2533 6004\nOvulatory infertility\nEndometriosis 148 296 2634 1617 4251\nUnexplained infertility 890 1780 8440 5828 14,268\nNot stated cause N/A N/A 12,797 7620 20,417\nTotal estimated number of couples needing IVF/ICSI 20,633 41,266 51,453 32,628 84,081\nTable 4  Infertility category results and total estimated and reported infertile population in Australia in 2019 with 20% infertility rate\n*Our analysis estimated the total number of IVF/ICSI cycles in 2019, including both fresh and thawed cycles.**Other female factors include \ninfertility caused by fibroids, ovulation disorders or premature ovarian failure Newman et al. [10]. Our analysis did not account for combination \nof female factors or a combination of male and female factors affecting fertility\nIndication for IVF/ICSI Estimated number of \ninfertile couples\nEstimated needed num-\nber of IVF/ICSI cycles*\nPerformed number of IVF/ICSI \ncycles\nFresh Thawed Total\nTubal obstruction 21,955 43,910 1462 1188 2650\nSevere male factor 13,722 27,444 5539 3888 9427\nAnovulatory infertility\nOvulation disorders (**other female factors) 8410 16,820 13,092 7121 20,213\nCombination of female factors N/A N/A 4018 2833 6851\nCombination of male and female causes N/A N/A 3471 2533 6004\nOvulatory infertility\nEndometriosis 334 668 2634 1617 4251\nUnexplained infertility 2003 4006 8440 5828 14,268\nNot stated cause N/A N/A 12,797 7620 20,417\nTotal estimated number of couples needing IVF/ICSI 46,424 92,848 51,453 32,628 84,081\n\n1790 Journal of Assisted Reproduction and Genetics (2024) 41:1783–1791\nLastly, from our population planning pregnancy, we deter-\nmined the annual number of infertile couples at our baseline \ninfertility rate (10%) and sensitivity analysis (16%).\nEstimating the Demand for IVF/ICSI\nThe total infertile population was divided into three categories, \naccording to the type of infertility diagnosed. Couples that \npresented unilateral or bilateral tubal obstruction as well as \nsevere male factor infertility were identified as couples with \nabsolute indications for IVF/ICSI treatment.\nAnovulatory infertility\nCouples that were diagnosed with ovulation disorders were \nclassified as couples with anovulatory infertility and under-\nwent hormonal treatment prior to IVF/ICSI.\nOvulatory infertility\nCouples that were diagnosed with ovulatory infertil-\nity included couples with unexplained infertility and \nendometriosis.\nTotal infertile population\n= population planning pregnancy × infertility rate\nCouples with absolute indications for IVF ∕ICSI\n= total infertile population ×( unilateral tubal obstruction prevalence\n+bilateral tubal obstruction prevalence\n+severe male factor infertility prevalence )\nCouples with absolute indications for IVF ∕ICSI\n= total infertile population ×(unilateral tubal obstruction prevalence\n+bilateral tubal obstruction prevalence\n+severe male factor infertility prevalence\nCouples with anovulatory infertility\n= total infertile population\n×ovulation disorder prevalence\nCouples with endometriosis = total infertile population\n× endometriosis prevalence\nCouples with unexplained infertility\n= total infertile population\n×unexplained infertility prevalence\nEstimated number of infertile couples in Australia\nThe number of couples requiring IVF/ICSI in Australia \nin 2019 is the sum of couples with absolute indications, \ncouples with anovulatory infertility with unsuccessful \npregnancies after hormonal treatment and couples with \novulatory infertility with unsuccessful pregnancies after \nIUI (Tables  3 and 4).\nAuthor contribution BWM conceived the idea for the study. MM was \nresponsible for data collection, data analysis, reviewing the literature \nand drafting the article. BWM and PTS supervised the entire study, \nincluding procedures, conception, design and completion as well as \nparticipated in the revisions and editing of the article. GJ reviewed and \nimproved visual figures of the article. All authors approved the final \nversion of the manuscript.\nFunding Open Access funding enabled and organized by CAUL and \nits Member Institutions.\nDeclarations \nCompeting interests MM declared no potential conflicts of interest \nwith respect to the research, authorship and/or publication of this \narticle. BWM is supported by a NHMRC Practitioner Fellowship \n(GNT1082548). BWM reports consultancy, research funding and travel \nsupport from Merck KGaA.\nOpen Access This article is licensed under a Creative Commons Attri-\nbution 4.0 International License, which permits use, sharing, adapta-\ntion, distribution and reproduction in any medium or format, as long \nas you give appropriate credit to the original author(s) and the source, \nprovide a link to the Creative Commons licence, and indicate if changes \nwere made. The images or other third party material in this article are \nincluded in the article’s Creative Commons licence, unless indicated \notherwise in a credit line to the material. If material is not included in \nthe article’s Creative Commons licence and your intended use is not \npermitted by statutory regulation or exceeds the permitted use, you will \nneed to obtain permission directly from the copyright holder. To view a \ncopy of this licence, visit http://creativecommons.org/licenses/by/4.0/.\nReferences\n 1. 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Accessed: Feb. 01, 2023.\nPublisher's Note Springer Nature remains neutral with regard to \njurisdictional claims in published maps and institutional affiliations.","source_license":"CC0","license_restricted":false}