Premenstrual Dysphoric Disorder

Between 2009–2015, naturally cycling women aged 18–47 (M = 32.70, SD = 8.21) with regular cycles (21–35 days) were recruited through flyers and emails seeking women with premenstrual emotional symptoms. Women were excluded for chronic medical disorders; histories of mania, substance dependence, or psychosis; any current SCID-I diagnosis; and certain medications (antidepressants, benzodiazepines, neuroleptics, or hormonal preparations). Participants were not paid. At a baseline visit, participants reported their medical and medication history and completed the SCID-I¹⁵ . Participants retrospectively reported the degree of premenstrual increase in each of 21 symptoms¹⁶ on a 4-point Likert scale from 1–No change to 4–Severe change (α = .91). Two hundred sixty-seven eligible women completed prospective assessment.
Prospective assessment included 2–4 cycles of daily DRSP ratings. Participants noted daily events they believed to have impacted daily mood; days in which participants reported the occurrence of a severe stressor not caused by symptoms were coded as missing. Participants mailed in forms weekly. In the final sample, 200 women provided at least two cycles. Eighty-five percent of women who dropped out after 1 cycle had not met C-PASS PMDD criteria in the first cycle. In women with >= 2 cycles, missing days were minimal (3.4%); just 1% of daily data were missing due to external events. Expert diagnoses (coauthor DR) of MRMD made prior to the development of the C-PASS (on the basis of identical data) were available for the majority of our sample (193 women; 96.5%). Because the DRSP summed total score demonstrates inadequate reliability of change¹⁷ , descriptive statistics for single items are considered.

Statistical analyses were performed under the direction of a bio-statistician (S.F.). Because our charge was to evaluate the current diagnostic criteria for PMDD taking into consideration the previous work done by the DSM-IV Work Group, we began with an exploration of what would constitute a menstrual-related symptom. In accord with the DSM-IV Work Group, we adapted the effect size method as illustrated by Hurt et al,^{8 (link)} which could measure the change between the postmenstrual and perimenstrual periods, yet retain a measure of background variability across the menstrual cycle. Hence, for each symptom, we computed an effect size as follows. We subtracted the postmenstrual follicular score (average ratings on days 7-12 after menses) from the perimenstrual score (average ratings during various 6-day intervals near menses) and divided the difference by the standard deviation of ratings during the entire cycle.
To test hypothesis 1 and identify the maximum follicular to perimenstrual phase change, we computed change scores using different permutations of the frame for perimenstrual symptoms. Specifically, we calculated effect sizes for various perimenstrual intervals: 6 days through 1 day before the onset of menses (days –6 through –1), 5 days before through the first day of menses (days –5 through 1), days –4 through 2, and days –3 through 3. To further assess the optimal time frame for perimenstrual symptoms, we tabulated functional impairment scores (eg, symptom effects on productivity and on relationships) during various days of the cycle to determine when functioning was most impaired. These items also were computed as effect sizes relative to follicular scores. For women with multiple cycles, cycles were averaged for this and other subsequent analyses.
To test hypothesis 2, the perimenstrual interval was days –4 through 2. A symptom was considered present if the effect size was 1.0 or greater.
To explore the optimal number of symptoms associated with distress and impairment for a premenstrual condition, symptoms were grouped into the following 11 DSM-IV categories: depressed mood, anxiety, mood swings/rejection, irritability/ anger, interest, concentration, lethargy, appetite, sleep, overwhelmed/out of control, and physical symptoms. Each of the 11 symptom groups (eg, sleep) was considered present if any of the constituent symptoms (eg, difficulty sleeping, slept more) had an effect size of 1.0 or greater. There were some symptoms (eg, chills) that we did not use. Criterion A of DSM-IV stipulates that at least 1 symptom must be a mood symptom (markedly depressed mood, feelings of hopelessness, or self-deprecating thoughts; marked anxiety, tension, feeling “keyed up,” or feeling “on edge”; marked affective lability; persistent and marked anger or irritability or increased interpersonal conflicts). Thus, if any of the first 4 symptoms in criterion A was present, then the number of PMDD symptoms was defined as the total across the 11 items. If none of the first 4 symptoms was present, then the number of PMDD symptoms was defined as 0 because the subject could not have functional impairment due to PMDD.
A woman was considered to have functional impairment if symptoms interfered with her ability to get things done at home, school, or work, with hobbies or social activities, or with her relationships with others. Impairment was considered present if any of the effect sizes was 1.0 or greater.
Cross-tabulations between the number of PMDD symptoms and functional impairment were generated and analyzed for the clinical sample, the community sample, and a combined sample with both samples weighted equally.
For each of the samples, sensitivity and specificity were computed corresponding to each potential cutoff point in the number of PMDD symptoms as a predictor of functional impairment. A suggested method for determination of the optimal cutoff point is to find the point with the maximum sum of sensitivity and specificity, or equivalently the maximum of Youden J statistic (sensitivity+specificity–1).¹⁴ Hosmer and Lemeshow¹⁵ suggest plotting sensitivity and specificity on the same graph and using the point where the curves cross as the optimal cutoff point, which tends to be consistent with using the Youden J statistic. Receiver operating characteristic curves were calculated as an overall measure of association between the number of PMDD symptoms and functional impairment.