Preconceptional Sex Selection Techniques

Number: 0323

Table Of Contents

Policy
Applicable CPT / HCPCS / ICD-10 Codes
Background
References

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Policy

Scope of Policy

This Clinical Policy Bulletin addresses preconceptional sex selection techniques.

1. Medical Necessity

   Aetna considers preconceptional sex selection techniques for enriching sperm samples for X spermatozoa medically necessary only when used to prevent the conception and birth of a male child to a woman who is known to be heterozygous for a seriously handicapping X-linked condition (e.g., Lesch-Nyhan disease).

   Assisted reproductive techniques, including in-vitro fertilization (IVF) or intra-cytoplasmic sperm injection (ICSI) are not considered treatment of disease when the sole indication for the procedure is sex selection and not to prevent birth of child with a seriously handicapping genetic defect.

2. Policy Limitations and Exclusions

   Note: The option of various post-sperm sorting infertility services (e.g., intra-uterine insemination, IVF, gamete intra-fallopian transfer [GIFT]) may be restricted depending upon the member's specific plan benefits. Aetna provides coverage for IVF and other assisted reproductive technologies (ART) to treat infertility, where required by state mandate and when the member's plan provides for such coverage. Please check benefit plan descriptions for details.

3. Related Policies

   • CPB 0140 - Genetic Testing
   • CPB 0327 - Infertility
   • CPB 0358 - Invasive Prenatal Diagnosis of Genetic Diseases

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Table:

CPT Codes / HCPCS Codes / ICD-10 Codes

Code	Code Description
Information in the [brackets] below has been added for clarification purposes.   Codes requiring a 7th character are represented by "+":
Preconceptional sex selection techniques:
No specific code
Other CPT codes related to this CPB:
58321	Artificial insemination; intra-cervical
58322	intra-uterine
58974	Embryo transfer, intrauterine
58976	Gamete, zygote, or embryo intrafallopian transfer, any method
88182	Flow cytometry, cell cycle or DNA analysis
88184	Flow cytometry, cell surface, cytoplasmic, or nuclear marker, technical component only; first marker
+ 88185	each additional marker (List separately in addition to code for first marker)
88187	Flow cytometry, interpretation; 2 to 8 markers
88188	9 to 15 markers
88189	16 or more markers
89261	Sperm isolation; complex prep (e.g., Percoll gradient, albumin gradient) for insemination or diagnosis with semen analysis
89268	Insemination of oocytes
89300	Semen analysis; presence and/or motility of sperm including Huhner test (post coital)
89310	motility and count (not including Huhner test)
89320	volume, count, motility, and differential
89321	Sperm presence and motility of sperm, if performed
96040	Medical genetics and genetic counseling services, each 30 minutes face-to-face with patient/family
Other HCPCS codes related to this CPB:
S0265	Genetic counseling, under physician supervision, each 15 minutes
S4011 - S4042	In vitro fertilization and related services

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Background

Primary sex selection (i.e., prior to fertilization using sperm sorting) has been suggested as an alternative to secondary sex selection (i.e., conception followed by prenatal diagnosis and abortion of affected fetuses) in couples known to be at increased risk for specific, detectable, heritable disorders. Preconceptional sex selection techniques have been proposed as a mechanism to minimize the risk of transmission of sex-linked diseases to potential offspring and are accomplished by differential sorting of X- and Y-bearing sperm using filtration and/or flow cytometry.

Sperm sorting techniques have been reported to result in samples enriched for X- or Y-bearing spermatozoa to levels as great as 75%. Although preconceptional sex selection through sperm sorting increases the likelihood of male or female offspring, it does not guarantee the sex of the fetus. Therefore, when medically indicated, invasive prenatal diagnostic procedures to confirm the sex of the fetus should be offered to the patient utilizing preconceptional sex selection techniques.

The American College of Obstetricians and Gynecologists Committee on Ethics (ACOG, 2007) presented various ethical considerations and arguments relevant to both pre-fertilization and post-fertilization techniques for sex selection. The principal medical reason for sex selection is known or suspected risk of sex-linked genetic disorders. Other reasons sex selection is requested are personal, social, or cultural in nature. The Committee on Ethics supports the practice of offering patients procedures for the purpose of preventing serious sex-linked genetic diseases. However, the committee opposes meeting requests for sex selection for personal and family reasons, including family balancing, because of the concern that such requests may ultimately support sexist practices. Because a patient is entitled to obtain personal medical information, including information about the sex of her fetus, it will sometimes be impossible for health care professionals to avoid unwitting participation in sex selection.

DeVilbiss et al. (2023) examined relationships between preconception adiposity and human offspring sex and sex ratio. Using data from a prospective, preconception cohort nested within a randomized controlled trial (RCT) based at four U.S. clinical sites (2006 to 2012), these researchers employed logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for male:female sex ratio, and log-identity regression to estimate risk differences (RDs) and 95% CIs for male and female live births according to preconception adiposity measures. Inverse-probability weights accounted for potential selection bias. Among 603 women attempting pregnancy, there were meaningful reductions in sex ratio for the highest category of each adiposity measure. The lowest sex ratios were observed for obesity (body mass index [BMI] of 30 or higher, calculated as weight (kg)/height (m)², OR = 0.48, 95% CI: 0.26 to 0.88) relative to normal BMI, and the top tertiles (tertile 3) of serum leptin (OR = 0.50, 95% CI: 0.32 to 0.80) and skin-fold measurements (OR = 0.50, 95% CI: 0.32 to 0.79) relative to the lowest tertiles. Reductions were driven by 11 to 15 fewer male live births per 100 women (for obesity, RD = -15, 95% CI: -23 to -6.7; for leptin tertile 3, RD = -11, 95% CI: -20 to -3.2; and for skin-folds tertile 3, RD = -11, 95% CI: -19 to -3.3). The authors concluded that relationships between elevated preconception adiposity markers and reduced offspring sex ratio were driven by a loss of male births among women attempting to conceive. Reductions in male births and in male:female sex ratios were consistent among women attempting pregnancy, among women who became pregnant, and among women with live births.

The authors stated that this study had several drawbacks. First, while these findings were generalizable to women with 1 to 2 pregnancy losses, pregnancy loss is common, occurring among one-third of human chorionic gonadotropin (hCG)-detected pregnancies, and these findings were likely to be underestimates or similar to what they would be among women unselected by loss history. Second, as this cohort was restricted to women attempting to conceive without the use of assisted reproductive technology (ART), these findings may not be generalizable to women attempting conception using ART. These investigators noted that this study was designed to examine population-level associations between adiposity and human sex ratio; thus, it did not have individual-level implications. Third, among 92 pregnancy losses in this sample, only 24 women (25 fetuses) had karyotype data on fetal sex. The lack of robust data on fetal sex of pregnancy losses precluded the ability to carry out a meaningful sensitivity analysis using these data. Fourth, leptin measures were taken from blood samples that were not universally fasting, although previous studies had shown that serum leptin was not sensitive to variations in fasting status. Fifth, subjects were predominantly White and of higher socioeconomic status, somewhat limiting the generalizability of these findings. These researchers stated that further investigations among diverse populations are needed.

The American College of Medical Genetics and Genomics (ACMG) Laboratory Quality Assurance Committee (Guha et al., 2024) outlines updated technical standards for clinical laboratories performing preconception and prenatal carrier screening, emphasizing that while high‑throughput microarray and next‑generation sequencing (NGS) technologies now enable the detection of a broad range of reproductive risks across numerous genes, these advances also introduce technical complexities that laboratories must manage. Their guidance underscores that carrier‑screening panels should maximize clinical sensitivity without overburdening clinicians or patients with genes lacking clear disease association or population relevance. To support this, the ACMG recommends a tiered carrier‑screening framework—tiers 1 through 4—based on carrier‑frequency thresholds, and advises offering all pregnant individuals and those planning pregnancy tier 3 screening, which includes tiers 1 and 2 along with 97 autosomal recessive and 16 X‑linked genes of high clinical relevance (e.g., DMD, FMR1). The document stresses the importance of reporting all pathogenic or likely pathogenic variants within these genes, while noting that adding conditions with carrier frequencies below 1/200 yields diminishing clinical benefit. As NGS‑based approaches gain broader implementation in diagnostic settings, laboratories remain responsible for panel design, validation, data generation, interpretation, and transparent reporting of assay strengths and limitations, including the need for ancillary testing where NGS performance is insufficient. Because sequencing technology is central to reliably assessing the large number of genes recommended by the ACMG, laboratories, healthcare systems, and electronic medical‑record developers are encouraged to innovate to reduce costs, enhance reimbursement pathways, and prevent redundant testing. The ACMG also cautions that laboratories should not claim compliance with tier 3 recommendations unless all required genes and variant types are fully assessed, and emphasizes that successful, equitable implementation of this tiered framework depends on continued collaboration among laboratories, clinicians, and stakeholders responsible for ordering and communicating carrier‑screening results.

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References