Outcomes after assisted reproductive technology in women with cancer: A systematic review and meta-Analysis

STUDY QUESTION: What are the associations between a history of cancer and outcomes after ART? SUMMARY ANSWER: Compared to women without cancer, on average, women with cancer had a lower return for embryo transfer and a lower likelihood of clinical pregnancy and live birth after ART. WHAT IS KNOWN ALREADY: Small, single-institution studies have suggested that cancer and its treatment may negatively affect ART outcomes. STUDY DESIGN, SIZE, DURATION: We conducted a systematic review with meta-Analysis of studies comparing ART outcomes between women with and without cancer. PubMed, Embase and Scopus were searched for original, English-language studies published up to June 2021. PARTICIPANTS/MATERIALS, SETTING, METHODS: Inclusion criteria required reporting of ART outcomes after controlled ovarian stimulation (COS) among women with a history of cancer compared to women without cancer who used ART for any indication. Outcomes of interest ranged from duration of COS to likelihood of live birth after embryo transfer. Random-effects meta-Analysis was used to calculate mean differences and odds ratios (ORs) with 95% CIs and 95% prediction intervals (PIs). We assessed heterogeneity by age-Adjustment, referent group indication for ART, study location and among women with breast cancer and women who initiated ART before cancer treatment. We used visual inspection, Egger's test and the trim-And-fill method to assess funnel plot asymmetry. MAIN RESULTS AND THE ROLE OF CHANCE: Of 6094 unique records identified, 42 studies met inclusion criteria, representing a median per study of 58 women with cancer (interquartile range (IQR) = 159) and 114 women without cancer (IQR = 348). Compared to women without cancer, on average, women with cancer had a lower return for embryo transfer (OR: 0.22; 95% CI: 0.07, 0.74; 95% PI: 0.00, 64.98); lower likelihood of clinical pregnancy (OR: 0.51; 95% CI: 0.35, 0.73; 95% PI: 0.19, 1.35); and lower likelihood of live birth (OR: 0.56; 95% CI: 0.38, 0.83; 95% PI: 0.19, 1.69). Substantial among-study heterogeneity was observed for COS duration, gonadotropin dose, cycle cancellation, total oocytes and mature oocytes. Fertilization percentage showed less heterogeneity, but study-specific estimates were imprecise. Similarly, number of embryos showed less heterogeneity, and most studies estimated minimal differences by cancer history. Funnel plot asymmetry was observed for estradiol peak and oocyte maturation percentage. LIMITATIONS, REASONS FOR CAUTION: Appreciable confounding is possible in 11 studies that lacked adequate control for group differences in age, and among-study heterogeneity was observed for most outcomes. Lack of data limited our ability to assess how cancer clinical factors (e.g. cancers other than breast, cancer stage and treatment) and ART cycle characteristics (e.g. fresh versus frozen embryo transfers and use of gestational carriers) may affect outcomes. WIDER IMPLICATIONS OF THE FINDINGS: Women with cancer may be less likely to achieve pregnancy and live birth after embryo transfer. Further examination of reproductive outcomes and sources of heterogeneity among studies is warranted to improve evidence of the expected success of ART after a cancer diagnosis. STUDY FUNDING/COMPETING INTEREST(S): This research was supported in part by R01 CA211093 and P30 ES010126. C.M. was supported by the University of North Carolina Lineberger Cancer Control Education Program (T32 CA057726) and the National Cancer Institute (F31 CA260787). J.A.R.-H. was supported by the National Cancer Institute (K08 CA234333, P30 CA016672). J.A.R.-H. reports receiving consulting fees from Schlesinger Group and Guidepoint. The remaining authors declare no competing interests. REGISTRATION NUMBER: N/A

Associations between Prenatal Urinary Biomarkers of Phthalate Exposure and Preterm Birth: A Pooled Study of 16 US Cohorts

Importance: Phthalate exposure is widespread among pregnant women and may be a risk factor for preterm birth. Objective: To investigate the prospective association between urinary biomarkers of phthalates in pregnancy and preterm birth among individuals living in the US. Design, Setting, and Participants: Individual-level data were pooled from 16 preconception and pregnancy studies conducted in the US. Pregnant individuals who delivered between 1983 and 2018 and provided 1 or more urine samples during pregnancy were included. Exposures: Urinary phthalate metabolites were quantified as biomarkers of phthalate exposure. Concentrations of 11 phthalate metabolites were standardized for urine dilution and mean repeated measurements across pregnancy were calculated. Main Outcomes and Measures: Logistic regression models were used to examine the association between each phthalate metabolite with the odds of preterm birth, defined as less than 37 weeks of gestation at delivery (n = 539). Models pooled data using fixed effects and adjusted for maternal age, race and ethnicity, education, and prepregnancy body mass index. The association between the overall mixture of phthalate metabolites and preterm birth was also examined with logistic regression. G-computation, which requires certain assumptions to be considered causal, was used to estimate the association with hypothetical interventions to reduce the mixture concentrations on preterm birth. Results: The final analytic sample included 6045 participants (mean [SD] age, 29.1 [6.1] years). Overall, 802 individuals (13.3%) were Black, 2323 (38.4%) were Hispanic/Latina, 2576 (42.6%) were White, and 328 (5.4%) had other race and ethnicity (including American Indian/Alaskan Native, Native Hawaiian, >1 racial identity, or reported as other). Most phthalate metabolites were detected in more than 96% of participants. Higher odds of preterm birth, ranging from 12% to 16%, were observed in association with an interquartile range increase in urinary concentrations of mono-n-butyl phthalate (odds ratio [OR], 1.12 [95% CI, 0.98-1.27]), mono-isobutyl phthalate (OR, 1.16 [95% CI, 1.00-1.34]), mono(2-ethyl-5-carboxypentyl) phthalate (OR, 1.16 [95% CI, 1.00-1.34]), and mono(3-carboxypropyl) phthalate (OR, 1.14 [95% CI, 1.01-1.29]). Among approximately 90 preterm births per 1000 live births in this study population, hypothetical interventions to reduce the mixture of phthalate metabolite levels by 10%, 30%, and 50% were estimated to prevent 1.8 (95% CI, 0.5-3.1), 5.9 (95% CI, 1.7-9.9), and 11.1 (95% CI, 3.6-18.3) preterm births, respectively. Conclusions and Relevance: Results from this large US study population suggest that phthalate exposure during pregnancy may be a preventable risk factor for preterm delivery

Towards the Development of an Interval Arithmetic Environment for Validated Computer-Aided Design and Verification of Systems in Control Engineering

Modern techniques for the design and analysis of control strategies for nonlinear dynamical systems are often based on the simulation of the open-loop as well as the closed-loop dynamical behavior of suitable mathematical models. In control engineering, continuous-time and discrete-time state-space representations are widely used which are given by sets of ordinary differential equations and difference equations, respectively. In addition to these representations, sets of differential algebraic equations are commonly used. Since we will focus on computational techniques which are applied for the design and mathematical verification of controllers for lumped parameter systems, i.e., systems which do not contain elements with distributed parameters, partial differential equations will not be considered in this talk. The prerequisite for the design and robustness analysis of each control system is the identification of mathematical models which describe the dynamics of the plant to be controlled as well as the available measurement devices with a sufficient accuracy. The model identification task comprises the derivation of physically motivated state equations, their parameterization based on measured data, as well as simplifications to apply specific approaches for controller design. In the design stage, both open-loop and closed-loop control strategies can be considered. Since dynamical system models are subject to uncertain parameters and uncertain initial conditions in most practical applications, detailed mathematical formulations of the desired dynamics of the controlled system are necessary. These specifications involve the definition of robustness with respect to the above-mentioned uncertainties. For linear system representations, robustness is commonly specified in terms of regions in the complex domain containing all admissible poles of the closed-loop transfer functions ($Gamma$-stability) or in terms of specifications of worst-case bounds for the frequency response ($mathcal{B}$-stability) [1]. However, these specifications do not allow for inclusion of bounds for the state variables which are often available in the time domain if controllers are designed for safety critical applications. Especially for nonlinear dynamical systems, pole assignment based on the linearization of nonlinear mathematical models generally leads to the necessity for the analysis of asymptotic stability of the resulting closed-loop dynamics. In this presentation, we will give an overview of the potential use of validated techniques for the analysis and design of controllers for nonlinear dynamical systems with uncertainties, where the systems under consideration will be subject to constraints for both state and control variables. As an application scenario the design of robust control strategies for a biological wastewater treatment process will be discussed. In the design and the verification process, constraints for both state and control variables which are given by guaranteed interval bounds in the time domain are taken into account. Suitable computational techniques are, for example, based on an extension of the validated initial value problem solver {sc ValEncIA-IVP} [2,6]. For that purpose, differential sensitivities of the trajectories of all state variables with respect to variations of the parameters of the mathematical system model as well as the adaptation of controller parameters are computed. This information can then be used for online identification and adaptation of parameters during the operation of a closed-loop controller as well as in offline design, verification, and optimization. Here, the interval arithmetic routines for sensitivity analysis allow to compute guaranteed differential sensitivity measures for system models with both nominal parameters and interval uncertainties. The presented interval arithmetic techniques are the basis for a general purpose tool for the analysis and the design of robust and optimal control strategies for uncertain dynamical systems. The presentation is concluded with an outlook on the formulation of control problems using sets of differential algebraic equations. Possibilities for the extension of {sc ValEncIA-IVP} to this type of system representation will be summarized. Relations between the presented interval arithmetic approach and methods for stabilizing control of nonlinear dynamical systems which make use of structural system properties such as differential flatness [3] and exact feedback linearization are highlighted [4,5]. In the latter case, input-output linearization as well as (in special cases) input-to-state linearization are of practical importance. References: [1] J. Ackermann, P. Blue, T. B"unte, L. G"uvenc, D. Kaesbauer, M. Kordt, M. Muhler, and D. Odenthal, {it{Robust Control: The Parameter Space Approach}}, Springer--Verlag, London, 2nd edition, 2002. [2] E. Auer, A. Rauh, E. P. Hofer, and W. Luther, {it{Validated Modeling of Mechanical Systems with {sc SmartMOBILE}: Improvement of Performance by {sc ValEncIA-IVP}}}, In Proceedings of Dagstuhl Seminar 06021: Reliable Implementation of Real Number Algorithms: Theory and Practice, Lecture Notes in Computer Science, Dagstuhl, Germany, 2006. In print. [3] M. Fliess, J. Lévine, P. Martin, and P. Rouchon, {it{Flatness and Defect of Nonlinear Systems: Introductory Theory and Examples}}, International Journal of Control, vol. 61, pp. 1327--1361, 1995. [4] H. K. Khalil, {it{Nonlinear Systems}}, Prentice-Hall, Upper Saddle River, New Jersey, 3rd edition, 2002. [5] H. J. Marquez, {it{Nonlinear Control Systems}}, John Wiley & Sons, Inc., New Jersey, 2003. [6] A. Rauh and E. Auer, {{www.valencia-ivp.com}}

Dreidimensionale Beurteilung der Brustzusammensetzung mit dem Automatisierten Brust Volumen Scanner (ABVS)

Studienziel: In der Bildgebung der Brust ist die Information für das Erkrankungsrisiko für die Brusterkrankung enthalten. Die mammografische Dichte oder der Drüsenanteil in der MRT- Untersuchung sind mit dem Brustkrebsrisiko bereits assoziiert worden. Graustufenwerte des B-Bildes im Ultraschall sind weiterhin mit der mammografischen Dichte assoziiert. Ziel dieser Untersuchung war es, die dreidimensionale Information der ABVS-Brustuntersuchung mit der mammografischen Dichte und dem Brustkrebsrisiko zu assoziieren. Methoden: Im Rahmen einer prospektiven Studie (BMBF-Spitzencluster BD04) zur Risikoprädiktion und Detektion von Brustkrebs wurden ABVS Aufnahmen (ACUSON S2000, SIEMENS) von 100 invasiven Mammakarzinomen und 100 Kontrollen gewonnen. An den gewonnenen dreidimensionalen Bilddaten sind Graustufenwertanalysen vorgenommen und zwischen den Fällen und Kontrollen verglichen worden. Weiterhin sind die Graustufenwerte mit der Mammografischen Dichte verglichen worden. Ergebnisse: Die Gewinnung und Verarbeitung der Bilddaten konnte im Rahmen der klinischen Routine für Patientinnen der allgemeinen Brustsprechstunde problemlos implementiert worden. Die komplette Erfassung der dreidimensionalen Daten dauerte im Durchschnitt 20 Minuten. Die detaillierte Analyse der Graustufenwerte wird vorgestellt. Schlussfolgerungen: Dreidimensionaler Ultraschall mittels ABVS kann unkompliziert in die klinische Routine implementiert werden. Die datentechnische Prozessierung und Analyse der Bilddaten ist unkompliziert und kann zu klinischen und wissenschaftlichen Zwecken verwendet werden

Analysis of recurrence probability following radiotherapy in patients with CNS WHO grade 2 meningioma using integrated molecular-morphologic classification

BackgroundThe current World Health Organization (WHO) classification of brain tumors distinguishes 3 malignancy grades in meningiomas, with increasing risk of recurrence from CNS WHO grades 1 to 3. Radiotherapy is recommended by current EANO guidelines for patients not safely amenable to surgery or after incomplete resection in higher grades. Despite adequately predicting recurrence probability for the majority of CNS WHO grade 2 meningioma patients, a considerable subset of patients demonstrates an unexpectedly early tumor recurrence following radiotherapy.MethodsA retrospective cohort of 44 patients with CNS WHO grade 2 meningiomas were stratified into 3 risk groups (low, intermediate, and high) using an integrated morphological, CNV- and methylation family-based classification. Local progression-free survival (lPFS) following radiotherapy (RT) was analyzed and total dose of radiation was correlated with survival outcome. Radiotherapy treatment plans were correlated with follow-up images to characterize the pattern of relapse. Treatment toxicities were further assessed.ResultsRisk stratification of CNS WHO grade 2 meningioma into integrated risk groups demonstrated a significant difference in 3-year lPFS following radiotherapy between the molecular low- and high-risk groups. Recurrence pattern analysis revealed that 87.5 % of initial relapses occurred within the RT planning target volume or resection cavity.ConclusionsIntegrated risk scoring can identify CNS WHO grade 2 meningioma patients at risk or relapse and dissemination following radiotherapy. Therapeutic management of CNS WHO grade 2 meningiomas and future clinical trials should be adjusted according to the molecular risk-groups, and not rely on conventional CNS WHO grading alone.MTG