Toward the Reliable Diagnosis of DSM-5 Premenstrual Dysphoric Disorder: The Carolina Premenstrual Assessment Scoring System (C-PASS)

Diagnostic Issues in Premenstrual Dysphoric Disorder

Characterized by the emergence of emotional symptoms in the luteal phase of the menstrual cycle, Premenstrual Dysphoric Disorder (PMDD) causes severe distress and impairment among the estimated 3–8% of women meeting DSM-5 criteria^1,2. Another 10–11% of women show evidence of a menstrually-related mood disorder (MRMD) causing distress and impairment sufficient to warrant treatment despite failure to meet full DSM-5 criteria². Due to the poor prospective validity of retrospectively-reported premenstrual symptoms, valid diagnosis requires evaluation of prospective daily symptom ratings³. In research settings, diagnosis is often made by visual inspection of daily symptom ratings⁷ (see Figure 1, Panel A). However, laboratories differ in the specific manner that daily ratings are translated into diagnostic decisions^8,9, and the complex, multilevel nature of the diagnosis suggests high risk of diagnostician error. These issues motivated development of the Carolina Premenstrual Assessment Scoring System (C-PASS), a standardized, computerized procedure for the reliable prospective diagnosis of DSM-5 PMDD.

The Complex, Multilevel Diagnosis of PMDD

DSM-5 PMDD is multifaceted and multilevel, requiring many conditions to be met (i.e., content, cyclicity, severity, and chronicity) at various levels (i.e., symptoms, cycles, women). DSM-5 symptoms and their overlap with the items of the Daily Record of Severity of Problems (DRSP)⁴, the most widely used daily symptom scale, are listed in Table 1. Table 2 outlines our conceptualization of DSM-5 diagnostic dimensions, including: (1) the content dimension, referring to the nature and number of symptoms; five symptoms must be present, of which one must be a core emotional symptom, (2) the cyclicity dimension, referring to both relative premenstrual elevation (“premenstrual change”) and absolute postmenstrual clearance of symptoms, describes the premenstrual onset and postmenstrual offset of symptoms in the perimenstrual timeframe⁵, (3) the clinical significance dimension, dictating that symptoms must be of sufficient absolute premenstrual severity and premenstrual duration as to cause clinically significant distress or impairment, and (4) the chronicity dimension, requiring symptoms to be present in the majority of months.

Translating DSM-5 Dimensions into Standardized Thresholds for the DRSP

The DRSP⁴ measures all 11 DSM-5 PMDD symptoms. Women rate daily symptoms on a 6-point scale from 1–Not at all to 6–Extreme. This allows for evaluation of symptom dimensions described above; however, DSM-5 does not give numeric thresholds for most dimensions, leading to variability in thresholds used across laboratories. Although the field has made some strides in standardizing diagnosis⁶, at least two key inconsistencies remain. First, the DSM-5 requirement of “severe” premenstrual symptoms (absolute severity) and “minimal or absent” postmenstrual symptoms (absolute clearance) is subjective, and different studies set this threshold for clinical significance of symptoms at different ratings on the DRSP⁷. The developers of the DRSP suggest that the most liberal acceptable delineation of “clinically significant” symptoms would be at greater than or equal to 4 (“moderate”)⁴. In order to reduce the risk of diagnosing normal affective experiences as a mental disorder^8–10, we recommend that this cutoff of “4-moderate” be implemented consistently as the threshold for absolute severity (premenstrual symptoms must reach 4) and absolute symptom clearance (postmenstrual symptoms must not exceed 3). Second, although 30% premenstrual elevation (or premenstrual “change”) is generally used^5,11 as the elevation threshold, at least five different methods have been used to calculate this premenstrual change variable (listed in Table 3 note)^{18,19,20,7,12,13}. Therefore, the present study begins by examining the interactive effects of both differing calculation methods and differing thresholds on diagnostic prevalence.

The Benefits of Computerizing Diagnosis

Even with validated numeric thresholds, many factors may limit the reliability of PMDD diagnoses made using visual inspection, making computerized diagnosis preferable. First, although it is possible to evaluate many of the diagnostic dimensions by simple visual inspection of daily ratings, premenstrual symptom elevation relative to one’s postmenstrual (follicular) symptoms—the most discriminating feature of PMDD¹¹—must be calculated for each symptom in each cycle. Second, validated numeric criteria have limited clinical utility if a clinician must calculate and concatenate the diagnostic dimensions “by hand” at symptom, cycle, and person levels across 1700 daily ratings (i.e., 3 months). Third, visual inspection of ratings across the entire cycle requires that the diagnostician ignore a great deal of distracting information that is not central to the diagnosis of PMDD. Finally, common errors of clinical judgment such as the tendency to ignore base rates (which in this case are low; 3–8% with PMDD and an additional 10–11% with non-PMDD MRMD^2,14) or assign too much importance to easily accessible information (e.g., absolute premenstrual symptom severity vs. the more complicated relative premenstrual symptom elevation) may introduce diagnostic error^10–12. Therefore, although valid diagnosis of PMDD is possible using simple visual inspection⁴, poor reliability of such visual diagnosis is likely due to busy clinician schedules and sources of unconscious error. It is this state of affairs that motivated our development of a computerized approach¹³ to making the complex diagnosis of PMDD.

Goals of the Carolina Premenstrual Assessment Scoring System (C-PASS)

This paper describes development of the C-PASS in a sample of 200 women seeking diagnosis with PMDD. We had four goals. First, by providing this standardized scoring system, we aim to promote the reliability—and, by extension, the construct validity—of the PMDD diagnosis by eliminating diagnostician variability and error. Given the important sociocultural considerations raised around the DSM-5 diagnosis, we feel that a move toward diagnostic specificity and reliability is critical^8–10. Second, C-PASS data output provides dimensional variables for each woman, with the goal of promoting the dimensional (vs. categorical) study of premenstrual dysphoria. Third, C-PASS visual output maximizes attention to central diagnostic information (see Figure 1, Panel B), with the goal of integrating the benefits of visual inspection with the reliability of computerization. Fourth, the C-PASS aims to improve the clarity of pathophysiological studies of PMDD by permitting more homogeneous clinical samples.

Description of the C-PASS Diagnostic Method

The C-PASS SAS Macro, Excel Macro, and worksheet are available at http://www.toryeisenlohrmoul.com/cpass. The macro code was developed using a double-coding technique by authors TAEM and JJ. The diagnostic process begins by characterizing each DRSP item in each cycle (where a cycle is defined as a set of contiguous premenstrual and postmenstrual weeks from consecutive cycles) using the four diagnostic dimensions as described in Table 2 (relative symptom elevation: percent symptom elevation during premenstrual week relative to the postmenstrual week >=30%; see Table 3, Method 2; absolute clearance: postmenstrual week maximum <=3; absolute severity: premenstrual week maximum >=4; and duration: severe premenstrual week days >=2). Because DSM-5 PMDD is defined as a marked on-off pattern occurring in the perimenstrual timeframe, the C-PASS utilizes the premenstrual week (defined as days −7 to −1, where −1 is the day prior to menstrual onset) and the postmenstrual week (defined as the 7 days following average menstrual offset: days 4 to 10, where day 1 represents menstrual onset). That is, the rationale for comparing the premenstrual week of one menstrual cycle to the contiguous postmenstrual week of the next cycle is to establish the “switch off” of symptoms, as it is critical to demonstrate that the cyclical symptoms do not persist into the follicular phase. Further, the C-PASS requires that at least 3 out of 7 ratings be present in each of the two weeks, and requires two cycles (i.e., perimenstrual frames).

While the DSM-IV research diagnosis of PMDD required premenstrual impairment, the DSM-5 no longer does. Therefore, the interference items on the DRSP are not included in the C-PASS, although information about the cyclicity and clinical significance of life interference items from the DRSP can be examined as secondary outcomes.

Next, cycle-level diagnosis of PMDD is made by counting DSM-5 symptoms meeting criteria on all four dimensions (Table 2; Total Symptoms: 1–4 for MRMD and >=5 for PMDD) and whether a core symptom meets criteria (number of core symptoms >=1). Next, MRMD or PMDD diagnosis is made at the person level by counting the number of cycles meeting MRMD and PMDD criteria (cycles meeting criteria >=2). Finally, the C-PASS creates a visual representation of relevant information for each DRSP item across as many cycles as provided (see Figure 1, Panel B), along with a determination of cycle-level diagnosis for that symptom in each cycle. The system also outputs a dataset with person-level summary variables for each symptom on each diagnostic dimension. In the present study, the more common research diagnosis of MRMD⁵ (i.e., 1–4 symptoms met for at least 2 cycles, of which one must be a core emotional symptom) was also calculated. Although the C-PASS diagnosis is designed to be made by a computer, a worksheet in the supplemental materials allows for manual replication of C-PASS diagnoses.

Participants, Procedure, and Materials

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.

Criterion Validity: Comparing C-PASS Diagnosis to Expert Diagnosis

Comparison of CPASS decisions (MRMD vs. no MRMD) to expert diagnosis revealed 94.3% agreement (11 disagreements). Inspection of ratings and clinical notes revealed three reasons for disagreement, each of which are instructive as to either the usefulness of the C-PASS or ways to improve the C-PASS moving forward.

In four cases, women were diagnosed by the C-PASS that were not diagnosed by expert clinician due to persistent background symptoms. Upon inspection of the raw data, the C-PASS had identified repeating cyclical patterns of anxiety (in 2 women) or interpersonal rejection sensitivity and anger (in 2 women). Of note, the DSM-5 does allow PMDD diagnosis to be made in such a case, so long as this pattern of symptoms does not represent an exacerbation of an underlying mood disorder, which were exclusionary in this study. Given (1) the clear evidence of repeating premenstrual elevations and postmenstrual declines on these symptoms and (2) the absence of Axis 1 disorder, we believe that the C-PASS decision for these women is accurate.

In three additional cases, women with insufficient premenstrual symptom severity (symptoms failed to reach a rating of “4–Moderate” in the premenstrual phase) or duration (less than two premenstrual days of at least moderate symptoms) were diagnosed with MRMD by the visual inspection that were not diagnosed by the C-PASS. Although these women showed genuine symptom cyclicity, they fail to meet the a priori definition of a mental disorder, and we feel that the C-PASS decision is accurate.

In the remaining four cases, women with “late” menstrual clearance of symptoms (symptoms persisting through the end of menses) were accurately diagnosed by expert clinician, whereas the C-PASS, which evaluates symptom clearance during days 4 to 10, failed to diagnose these women because it judged that symptoms had not cleared adequately. We feel that the expert clinician was correct in these cases, and this provides an important area for improving the C-PASS. In a future study (for which data collection is underway), we will evaluate differences between (1) diagnosis made based on standardized days 4 to 10, and (2) diagnosis made based on an individualized last day of menses +7 days. Although the latter may seem the intuitive choice, the former may have the benefit of greater biological validity, as the start of menstrual bleeding is a less ambiguous stimulus to self-report than the end of menses. In sum, we feel that the C-PASS mistakenly failed to diagnose just 4 women (2% of sample).

Comparison of Retrospective Premenstrual Symptoms to C-PASS Diagnosis

Consistent with previous reports¹⁶, logistic regression revealed that retrospectively-reported premenstrual symptom change was a very poor predictor of both C-PASS MRMD diagnosis (Standardized B = .038, SE = .011, X² = 11.46, p = .0007, OR for a 1 SD increase in retrospective symptoms = 1.03, 95% CI: 1.01 to 1.06) and C-PASS PMDD diagnosis (Standardized B = .061, SE = .016, X² = 14.01, p = .0002, OR for a 1 SD increase in retrospective symptoms = 1.06, 95% CI: 1.03 to 1.09). Given this poor predictive validity of retrospectively reported premenstrual symptoms, attempts to identify a reasonably sensitive and specific cutoff value for the prediction of C-PASS diagnoses were unsuccessful (AUC for MRMD Diagnosis= .63, 95% CI: .56 to .70; AUC for PMDD Diagnosis = .70, 95% CI: .62 to .78).

Limitations and Future Directions

Several limitations of this study are noteworthy: First, because the C-PASS is designed to identify premenstrual symptoms of a clinically significant nature, it may therefore fail to identify women who demonstrate significant menstrual-cycle entrainment of symptoms that are not premenstrual (e.g., at midcycle), or those who do not show sufficient absolute severity or clearance. Second, because the C-PASS seeks to balance efficiency with reliability, it does not consider mid-cycle symptoms; if significant late follicular symptoms are present, this may signal the need for differential diagnosis. Third, the C-PASS is developed for the DRSP, given that this scale assesses all DSM-5 content; however, other useful rating scales for PMDD exist (e.g., the Daily Symptom Record²⁴). Limitations of the DRSP, such as scale sensitivity (i.e., relative to a 100mm scale) and unbalanced content coverage should be addressed. Fourth, the C-PASS may fail to accurately diagnose some women with late symptom clearance; future work should determine whether self-reported menstrual offset is sufficiently accurate to permit the use of personalized postmenstrual weeks for each woman. Additional validation work must demonstrate that the methods and thresholds selected here are calibrated to ensure only the diagnosis of women who need treatment. Finally, women seeking treatment for PMDD in clinical settings may prove to be qualitatively different from women in research settings.

Research Applications

The C-PASS has myriad applications in research. In the context of clinical research, the use of a standardized, reliable system of diagnosis would ensure shared diagnostic meaning across laboratories, and would ensure homogenous samples. The C-PASS also allows for dimensional characterization of symptoms across samples, individuals, and cycles according to four central dimensions of PMDD diagnosis (see Table 2), which may allow for the eventual identification of meaningful differences, if any, between women with PMDD and other MRMDs. Further development of this system may allow for the identification of distinct subgroups with differing pathophysiology²². Finally, it should be noted that the C-PASS can also be used to identify cycles meeting criteria for PMDD, a feature that could be useful for defining treatment response.

Clinical Implications

There are currently no reliable and valid diagnostic procedures for PMDD that are feasible for widespread clinical application. Given the time involved in prospective assessment, nearly 90% of clinicians who treat PMDD rely on patient retrospective self-report, which we know to be prone to false positives, to make diagnoses¹⁹. This is troubling when considered in tandem with the present evidence that (1) there is a relatively low prevalence of true PMDD even among women seeking assessment for premenstrual symptoms, and (2) variability on retrospective self-report of premenstrual symptoms does not provide information about whether a standardized, prospective diagnosis of PMDD is present. Rigorous experimental²³ and longitudinal¹⁴ studies have established the biological validity of PMDD, and treatments are available; however, assessments that combine validity, reliability, and efficiency need to be developed so that women with the disorder can receive treatment, and women without the disorder can search for alternative causes of their symptoms. Standardization of research diagnoses through the C-PASS represents an initial step toward development of efficient and reliable clinical tools. The current C-PASS materials may be immediately useful clinically; however, additional development is needed to digitize data collection and streamline the diagnostic process for clinical application.