Introduction and Objectives:
The objective of our study was to examine the significance of assessment of sperm DNA damage in predicting the outcome of ART in couples with male factor infertility.
Methods:
Ninety-two infertile couples with normal female partners were included in this study. A group of fertile donors (n =16) served as controls. Standard semen analysis was performed according to the World Health Organization (WHO) guidelines. Levels of sperm nuclear DNA damage were determined by sperm chromatin structure assay. Thirty-three out of the 92 couples underwent ART procedures [intrauterine insemination (IUI) (n = 19), in-vitro fertilization (IVF) (n = 10), or intra-cytoplasmic sperm injection (ICSI) (n = 4)], while the remaining 59 did not.
Results:
Sperm DNA damage (%COMPαt) and motility were significantly correlated with pregnancy (P = 0.04 & 0.03). Levels of DNA damage were negatively correlated with pregnancy, naturally (P = 0.01, r = 0.5), or through IUI (P =0.01, r = 0.5), IVF (P = 0.009, r = 0.7), but not ICSI (P = 0.2). No pregnancy was reported at DNA damage > 28%, naturally or through any ART. The diagnostic measures of sperm DNA damage and motility to predict pregnancy in couples with male factor infertility are illustrated in the table.
Conclusions:
Sperm DNA damage test may be a potential tool for predicting the outcome of ART in couples with male factor infertility. Since level of DNA damage >28% is inconsistent with initiation of pregnancy, it may be wise to consider canceling an ART cycle when sperm DNA damage exceeds this level.
|
|
Sensitivity |
Specificity |
PPV |
NPV |
P |
|
All patients (n = 92) |
|
|
|
|
|
|
DNA Damage <28% |
100 |
43 |
19 |
100 |
0.04 |
|
Motility ≥50% |
82 |
56 |
20 |
96 |
0.03 |
|
Patients attempting ART (n = 33) |
|
|
|
|
|
|
DNA Damage <28% |
100 |
58 |
47 |
100 |
0.04 |
|
Motility ≥50% |
78 |
71 |
50 |
89 |
0.03 |
|
PPV = positive predictive value; NPV = negative predictive value; P = p-values from logistic regression using DNA damage (%) and motility (%) as continuous variables to predict pregnancy |
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