Pain catastrophizing is associated with pain thresholds for heat, cold and pressure in women with chronic pelvic pain

Background and aims: Psychological traits such as pain catastrophizing may play a role in the development of chronic pelvic pain (CPP). Pain catastrophizing is the ten- dency to amplify negative cognitive and emotional pain processes. The Pain Catastrophizing Scale (PCS) assesses elements of pain catastrophizing divided into three sub - groups of factors (rumination, helplessness and mag - nification). Previous studies have shown associations between CPP and increased pain sensitivity, widespread generalized hyperalgesia, and decreased pain thresholds, but the relation between pain catastrophizing and specific pain thresholds has not yet been widely examined in this patient group. The aims of this study were (a) to determine if catastrophizing is increased in women with CPP com- pared with pain-free women, (b) to assess the importance of pain catastrophizing, psychological distress variables, and subjective pain sensitivity for pain thresholds of heat, cold and pressure in these two groups, and (c) to deter - mine whether psychological variables or pain thresholds best contribute to the differentiation between CPP and controls.

Thirty-seven women with chronic pelvic pain who underwent diagnostic laparoscopy on the suspicion of endometriosis participated along with 55  healthy and pain-free controls. All underwent quantitative sensory testing on six locations on the body to determine heat (HPT), cold (CPT) and pressure (PPT) pain thresholds. The PCS, the Pain Sensitivity Questionnaire (PSQ), the Hospital Anxiety Depression Scale, (HADS) demographics and clinical data were collected prospectively. Principal component analysis and orthogonal partial least square regressions were used to assess the associations between PCS scores and pain thresholds.

The women with CPP scored significantly higher on PCS than the healthy controls. PCS-helplessness, PCS- rumination and HADS-depression were significantly associated with pain thresholds for the whole group. In the CPP group, PCS-rumination, body mass index and PSQ were significant regressors for HPT and CPT. The PCS and the HADS subscales were strongly intercorrelated in women with CPP and were stronger regressors of group membership than the three pain thresholds. In the group of healthy control women, no relationships were found to be significant. The psychological variables were some- what stronger significant regressors than pain thresholds (also significant) for group membership.

Women with CPP have significantly higher pain catastrophizing scores than women without CPP . The pain catastrophizing rumination factor is significantly associated with pain thresholds of heat and cold in CPP women. PCS and HADS are strongly intercorrelated and PSQ correlates positively with these variables. It seems that the psychological variables are important for group differentiation. Implications: The results clearly indicate the need for a multimodal assessment (bio-psycho-social) of CPP patients including psychological symptoms such as cata- strophizing, anxiety and depression. The registration of semi-objective pain thresholds captures both specific pain *Corresponding author: Hanna Grundström, Department of Obstetrics and Gynaecology in Norrköping, and Department of Biomedical and Clinical Sciences, Linköping University, Norrköping, Linköping, Sweden; and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden, E-mail: [email protected] Britt Larsson and Björn Gerdle: Pain and Rehabilitation Centre, and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden Lars Arendt-Nielsen: Center for Sensory-Motor Interactions, Department of Health Science and Technology, Faculty of Medicine, Aalborg University, Aalborg, Denmark Preben Kjølhede: Department of Obstetrics and Gynaecology in Linköping, and Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden © 2020 Scandinavian Association for the Study of Pain. Published by Walter de Gruyter GmbH, Berlin/Boston. All rights reserved. Sc and J Pain 2020; 20(3): 635–646 Published online May 09, 2020 sensitivity information (mechanical pressure, cold or heat) and the degree of wide spread pain hypersensitivity. There is a need for future larger studies investigating whether certain profiles in the clinical presentations (including pain thresholds and psychological variables) are associ- ated with outcomes after different types of interventions.

chronic pelvic pain; catastrophizing; PCS; pain thresholds. 1 Introduction Chronic pelvic pain (CPP) is common in women of repro - ductive age [1]. It often originates from multifactorial mechanisms and can manifest as dysmenorrhoea or endo- metriosis [2]. Chronic pain can lead to widespread reduced pain thresholds, i.e. generalized pain hypersensitivity. By definition, pain hypersensitivity as presented by reduced pain thresholds represents an abnormal state of respon- siveness in the nociceptive pain system [3]. Pain hypersen- sitivity can be assessed with Quantitative Sensory Testing (QST), a set of psychophysical tools to assess mechanisti- cally the status of the nociceptive and non-nociceptive pathways. The tests commonly include cold, heat and pres- sure thresholds, pain detection thresholds or pain toler - ance thresholds [4]. QST has been used to investigate pain sensitivity in women with CPP and has shown increased and/or widespread hyperalgesia, elevated sensory thresh- olds and myofascial trigger points [5–10]. These results may indicate that CPP may be defined as nociplastic pain, the recently defined new type of pain mechanism defined by the International Association of the Study of Pain [11]. The perception of pain is integrated with psychologi- cal traits and pain coping behaviour and interacts with QST assessments [12]. Increased anxiety, depression and perceived pain sensitivity correlate with reduced pain thresholds [13–16]. Emotional dysregulation has been implicated as a transdiagnostic risk factor for pain sever - ity and mood aspects [17 , 18]. Emotion regulation, e.g. cat- astrophizing, is a trans-diagnostic process that ties pain and depression/emotion [19–21]. Pain catastrophizing is the tendency to amplify negative cognitive and emotional processes related to pain. It influences the sensation of pain [12] and may be a risk factor for the development of chronic pain after surgery [22]. Pain catastrophizing may act as a predictor of chronic pain among women with CPP [23–25] or endometriosis [26, 27] and in young women with menstrual pain [28]. Moreover, catastrophizing is one of several contributors to the severity of CPP [29] and to reduced quality of life [24]. CPP patients with high catastrophizing showed worse outcomes after different treatments compared with those with low catastrophiz - ing [25]. The relationship between pain catastrophizing and pain thresholds in various chronic pain conditions has not been definitively established [30]. A deeper understand - ing of how pain mechanisms are related to psychological factors is essential for the planning and management of effective care for women with CPP . We have reported that women with CPP had alterations in pain thresholds indi- cating widespread hypersensitivity, and a time-dependent correlation between pain thresholds and duration of the CPP . In addition, the pain thresholds were significantly correlated with pain sensitivity [10, 16]. The aims of this study were (a) to determine if cata- strophizing is increased in women with CPP compared with pain-free women, (b) to assess the importance of pain catastrophizing, psychological distress variables, and sub- jective pain sensitivity for pain thresholds of heat, cold and pressure in these two groups, and (c) to determine whether psychological variables or pain thresholds best contribute to the differentiation between CPP and controls. 2 Methods 2.1 Study design and sample This is a secondary analysis of the data from a cross- sectional observational comparative study that was con- ducted between December 2013 and June 2016 at the Department of Obstetrics and Gynaecology at a central hospital and a university hospital in southeast Sweden [10]. The study was approved by the Regional Ethics Board of Linköping University (Reg.no. 2013/19-3). In summary, pain thresholds for heat, cold and pres - sure were prospectively measured in 37  women with CPP referred for diagnostic laparoscopy due to symptoms that could indicate endometriosis, and in 55  healthy women without CPP . All participants filled in the PCS form, the Pain Sensitivity Questionnaire (PSQ) and the Hospital Anxiety and Depression Scale (HADS) form. A detailed description of the study is presented in the original study [10]. 2.2 Measurements 2.2.1 Pain Catastrophizing Scale (PCS) The PCS is a self-administered questionnaire consist - ing of 13 items divided into three domains: helplessness, magnification, and rumination. The questions cover the 636 Grundström et al.: Pain catastrophizing is associated with pain thresholds patient’s thoughts and feelings in different painful situ - ations and include information on both intensity and fre- quency. The items are answered on a five point Likert-type scale using the phrases: not at all (0), to a slight degree (1), to a moderate degree (2), to a great degree (3), and all the time (4). The scores for the three domains are summarised by different items: magnification relates to items 6, 7 and 13, rumination to items 8–11, and helplessness to items 1–5 and 12 [31]. Higher scores indicate a greater tendency for catastrophizing. The Swedish version of the PCS has been validated [32]. 2.2.2 Pain Sensitivity Questionnaire (PSQ) In the PSQ [14] the patient grades the imagined painful - ness of 14 described painful everyday situations, where the situations include different pain types such as blunt, cold, hot and sharp, and are divided into different inten- sities and body sites. Three items serve as non-painful sensory references. The average rating is the PSQ total score, which is calculated from all painful items. A higher PSQ score indicates higher perceived pain sensitivity [14]. 2.2.3 Hospital Anxiety and Depression Scale (HADS) The HADS is a self-rating test assessing symptoms of anxiety and depression using 14 items divided into two, seven items subscales (anxiety subscale and depression subscale) [33]. The subscale scores range between 0 and 21 points, with higher scores indicating more symptoms of anxiety or depression. The Swedish version has been validated [34]. 2.2.4 Quantitative Sensory Testing (QST) Pain thresholds for heat, cold and pressure were meas - ured on six body sites using QST [35] according to the guidelines proposed by the German Research Network on Neuropathic Pain, with minor deviations [36]. The body sites were: the abdominal wall, seven cm lateral to the umbilicus on both sides, the abdominal wall just above the symphysis pubis, five cm lateral to the midline on both sides, the medial plane of the low back just below the fifth lumbar vertebra, and on the dominant leg, four cm dis - tally from the tuberositas tibiae (the control area). Heat (HCP) and cold (CPT) pain thresholds were measured with The Medoc TSA II NeuroSensory Analyzer (Medoc Ltd. 1 Ha’dekel St. Ramat Yishai 30095 Israel) using a 3 × 3  cm 2 computer-controlled thermode. The temperature dropped or increased from 32 °C at a rate of 1.5 oC/s to a maximum of 50 °C, or a minimum of 0 °C. The participant stopped the stimulation when first detecting a painful stimulus. Pressure pain threshold (PPT) measurements were performed using a hand-held electronic algometer (Sometic AB, Hornby, Sweden) with a pressure surface area of 1  cm 2. Pressure was applied at a rate of approxi- mately 40 kPa/s and was discontinued on the first sensa- tion of pain. Three measurements of each stimulus were performed on each body site and the arithmetic average was pre- sented as the pain threshold [35]. The testing order of both body sites and stimuli was altered randomly. The majority of the measurements were performed by the first author, and the rest by three research nurses experienced in QST. 2.3 Statistical analyses Statistical analyses were conducted with the software Sta- tistica v 13.1 (Dell Software, 5 Polaris Way, Aliso Viejo, CA 92656, USA) and the SIMCA-P software version 15 (Umet - rics, Sartorius Stedim Biotech, Umeå, Sweden). Data are presented as median and interquartile range (IQR) or fre- quency (number and percent). A between-group comparison of demographic char - acteristics, clinical characteristics, pain thresholds and questionnaire data was conducted using a Mann-Whitney U-test for continuous data and Pearson’s chi-squared test or Fisher’s exact test for nominal data. The level of statis- tical significance was set at p  < 0.05 for two-sided tests. Due to the risk of downplaying the interrelation- ship among factors and thus reaching incorrect conclu - sions when using classic statistical methods (for instance linear regression), and the obvious risk of multicollin- earity problems when using psychological variables, we used advanced multivariate data analysis (MVDA) as elaborated more in detail elsewhere [16]. The MVDA in the present study consists of principal component analy - sis (PCA) to detect outliers, and orthogonal partial least square regressions (OPLS) for the multivariate regressions. OPLS discriminant analysis (OPLS-DA) is used to show which variables have the largest discriminatory power for group separation (i.e. CPP vs. controls). Methods such as multiple linear regression assumes that the independent variables (x-variables, regressors) are not strongly inter - correlated i.e. multicollinearity is not present. Based on previous research we had good reasons to suspect the presence of multicollinearity. OPLS is instead based upon Grundström et al.: Pain catastrophizing is associated with pain thresholds 637 the assumption that the independent variables may be intercorrelated (in unknown ways) and takes advantage of this multicollinearity pattern. The data is not required to be normally distributed when applying these methods of MVDA [37]. Basically, the MVDA R 2 describes the goodness of fit – the fraction of sum of squares of all the variables explained by a prin- cipal component. Q 2 describes the goodness of prediction – the fraction of the total variation of the variables that can be predicted by a principal component using cross- validation methods [38]. A check for outliers was conducted using score plots of the PCA in combination with Hotelling’s T 2, and dis - tance to model in X-space [38]. No extreme outliers were detected in the present study. PCA can be regarded as a multivariate correlation analysis. Instead of performing multiple bi-variate correlations a PCA analysis is per - formed and the risks associated with multiple testing is markedly reduced. Besides checking for multivari- ate outliers PCA ’s were made in order to understand the correlation pattern among the variables used as regres - sors (x-variables). Graphic presentations implemented in SIMCA-P software were used to facilitate the understand - ing of the correlation pattern. OPLS was used to explore the relative roles of PCS sub- scales, HADS subscales and PSQ together with background data (age, BMI, and smoking) to explain the variations in the pain thresholds for each stimulus [38]. A variable influ- ence on projection (VIP) ≥ 1.0 was considered significant if the VIP value had a 95% jack-knife uncertainty confi- dence interval non-equal to zero [38]. P(corr) depicts the loading of each variable scaled as a correlation coefficient, thus standardising the range from −1 to + 1. An absolute p(corr) > 0.4–0.5 is generally considered significant [37]. VIP values are specific for a certain regression but can be compared within a regression i.e. between the x-variables (regressors). P(corr) is suitable for comparisons between regressions but require that the same dependent variable (Y-variable) is used. For each regression, we report the R 2, Q2, and the result (i.e. p-value) of a cross-validated analysis of variance (CV-ANOVA). In the present study we required a significant CV-ANOVA for a regression to be significant. A certain variable was considered a significant variable when VIP > 1.0 and absolute p(corr) ≥ 0.50. 3 Results The demographic and descriptive data and the scores of the psychometric instruments for the 37 CPP women and the 55 controls are presented in Table 1. The CPP women deviated significantly from the control women in all Table 1: Demographics, clinical characteristics, pain thresholds for heat, cold and pressure, PCS subscales, HADS subscales and PSQ total scores of women with chronic pelvic pain and healthy controls. Variable   Women with chronic pelvic pain (n = 37)   Control group of healthy women (n = 55)  p-value Age (years)   25.0; 22–30   31.0; 25–35   0.002 BMI (kg/m2)   23.7; 20.8–26.8   23.9; 21.1–25.7   0.796 Nulli-parous (no. of women)   30 (81)   24 (44)   0.014 Currently smoking (no. of women)  9 (24)   2 (4)   0.006 Hormonal birth control medication (no. of women)   20 (54)   34 (62)   0.520 Duration of pelvic pain (months)   36.0; 16–78   –   Heat pain threshold (°C)   44.6; 41.0–47.2   47.8; 46.6–49.1  <0.001 Cold pain threshold (°C)   10.5; 6.3–20.5   0.59; 0.0–6.9  <0.001 Pressure pain threshold (kPa)   290.8; 227.3–434.8   553.0;401.5–654.8  <0.001 PCS rumination   11.0; 10.0–12.8   4.0; 1.8–7.0  <0.001 PCS magnification   5.5; 4.0–8.0   2.0; 1.0–4.0  <0.001 PCS helplessness   13.5; 11.0–18.0   3.0; 1.0–5.3  <0.001 HADS anxiety   10.0; 7.0–12.0   4.0; 2.0–7.0  <0.001 HADS depression   8.0; 5.0–11.0   2.0; 1.0–3.0  <0.001 PSQ   4.6; 2.6–4.1   3.6; 3.4–5.3  <0.001 Furthest to the right is shown the between-group comparisons (p-value). Figures denote median; 25th–75th interquartile range or number of women and (%). BMI = Body Mass Index; PCS = Pain Catastrophizing Scale; PCS rumination = rumination scale of PCS; PCS magnification = magnification scale of PCS; PCS helplessness = helplessness scale of PCS; HADS = Hospital Anxiety and Depression Scale; HADS-Depression = depression scale of HADS; HADS-anxiety = anxiety scale of HADS; PSQ = Pain Sensitivity Questionnaire – total index. 638 Grundström et al.: Pain catastrophizing is associated with pain thresholds variables accounted for except for BMI and use of hormo - nal birth control. The median duration of pelvic pain in the CPP women was 36 months (IQR 18–72 months). Likewise, and as reported earlier for these two cohorts [10, 16] the pain thresholds were significantly lower in the CPP group. 3.1 Catastrophizing – group comparisons Catastrophizing scores were significantly higher in the CPP women than in the healthy control women according to the three aspects (subscales) captured by PCS (Table 1). 3.2 Regressions of pain thresholds 3.2.1 Regressions of pain thresholds – all subjects taken together The associations between the three pain thresholds (y-var- iables) and the other variables (x-variables) were investi- gated in three regressions (Table 2). Highly significant regressions (R 2: 0.30–0.45; all CV-ANOVA p < 0.001) were obtained for the three pain thresholds. A mix of variables showed important associations with the three investi- gated thresholds. The three analyses presented in Table 2 had in common that PCS-helplessness, PCS-rumination and HADS-depression were significantly associated with the pain thresholds. The three scales of PCS and the two scales of HADS were important regressors correlating negatively with PPT. Two PCS scales (i.e. helplessness and rumination) were the most important regressors. In summary, psycho- logical distress and catastrophizing were associated with low PPT when analysing all subjects taken together. Both scales of HADS, PSQ and the three PCS scales were positively associated with CPT (Table 2). Depressive symptoms according to HADS and PSQ followed by two PCS scales (i.e. helplessness and rumination) were the variables most strongly correlated with CPT. For HPT, a negative association with PSQ, the depres- sion subscale of HADS and two of the PCS scales (i.e. help- lessness and rumination) were found (Table 2). 3.2.2 Regressions of pain thresholds in women with CPP Among women with CPP , the regression of PPT did not reach significance according to the CV-ANOVA (Table 3). Two of the subscales of PCS together with PSQ tended to be most important for PPT. Table 2: OPLS regressions of PPT, CPT and HPT in all subjects taken together (n = 92), i.e. women with CPP and healthy control women. PPT – all subjects CPT – all subjects HPT – all subjects Variables VIP p(corr) Variables VIP p(corr) Variables VIP p(corr) PCS-helplessness 1.31  −0.88 HADS-depression 1.26 0.73 PSQ 1.39  −0.79 PCS-rumination 1.27  −0.85 PSQ 1.25 0.72 PCS-rumination 1.19  −0.67 PCS-magnification 1.22  −0.82 PCS-rumination 1.16 0.67 HADS-depression 1.14  −0.64 HADS-anxiety 1.19  −0.79 PCS-helplessness 1.12 0.65 PCS-helplessness 1.11  −0.63 HADS-depression 1.16  −0.78 HADS-anxiety 1.05 0.60 PCS-magnification 0.98 −0.55 PSQ 0.91 −0.60 PCS-magnification 1.02 0.59 HADS-anxiety 0.96 −0.54 Age 0.64 0.43 BMI 0.89 0.52 BMI 0.88 −0.50 Smoking 0.39 −0.26 Smoking 0.52 0.30 Smoking 0.57 −0.32 BMI 0.07 −0.05 Age 0.22 −0.12 Age 0.34 0.19 R2 0.30 R2 0.45 R2 0.43 Q2 0.27 Q2 0.36 Q2 0.35 CV-ANOVA p-value <0.001 CV-ANOVA p-value <0.001 CV-ANOVA p-value <0.001 Number of subjects (n) 92 Number of subjects (n) 92 Number of subjects (n) 92 Note that pain duration was not included in the regression since it defines the two groups of subjects. Variables with VIP > 1.0 and absolute p(corr) > 0.50 are significant and shown in bold type. The sign of p(corr) indicates the direction of the correlation with the dependent variable (+ = positive correlation;  −   = negative correlation). The four bottom rows of each regression report R 2, Q2, p-value of the CV-ANOVA and number of subjects (n). PPT = mean value of pressure pain thresholds; CPT = mean value of cold pain thresholds; HPT = mean value of heat pain thresholds; BMI = body mass index; Smoking = currently smoking (i.e. dummy variable: smoking = 1, non-smoking = 0); HADS = Hospital anxiety and depression scale; HADS-Depression = depression scale of HADS; HADS-anxiety = anxiety scale of HADS; PCS = Pain Catastrophizing Scale; PCS-helplessness = helplessness scale of PCS; PCS-rumination = rumination scale of PCS; PCS-magnification = magnification scale of PCS; PSQ = Pain Sensitivity questionnaire – total index. Grundström et al.: Pain catastrophizing is associated with pain thresholds 639 For the two significant regressions of the thermal pain thresholds (R2: 0.51–0.52; CV-ANOVA p-value: 0.029– 0.049) it was found that the same variables were signifi- cant regressors even though their relative importance differed somewhat (Table 3). Hence, BMI, PSQ and the rumination subscale of PCS were the three significant regressors; the three variables correlated positively with CPT and negatively with HPT. BMI and PSQ were rela- tively equally important while the PCS rumination scale in both analyses had less importance even though it was significant. 3.2.3 Regressions of pain thresholds in healthy control women No significant regressions were found for any of the three pain thresholds in the healthy control women (data not shown). 3.2.4 Intercorrelations among the independent variables (the regressors) We also investigated the intercorrelation pattern among the variables used as regressors (x-variables) in the regressions above (Tables 2 and 3). Bivariate correlation analyses both for all subjects together and separate for the two groups clearly indicated intercorrelations between the independent variables (Supplementary Table S1). However, the interpretations of these are complicated and therefore multivariate correlation analyses by means of PCA were performed to investigate whether the regressors represented one or several groups of variables (latent vari- ables or components). In all subjects taken together, the PCA resulted in one significant component (R 2 = 0.45; Q2 = 0.32) (Fig. 1). Figure 1 shows the two HADS scales and the three PCS scales as highly positively intercorrelated (they had the same sign and had high p -values according to the first component [p1 =  the horizontal axis]). PSQ also had a relatively high loading on p1 but was more distant to the six psychological variables and was less strongly correlated with them. Smoking, BMI, and age had low absolute loadings (< 0.22) upon p1 and thus were not so important. Note that the second component p2 (verti- cal axis) in Fig. 1 was not significant. In Supplementary Figure S1 the three pain thresholds are included in the PCA. Also, in the CPP (Fig. 2), PCA resulted in one signifi- cant component (R 2 = 0.31, Q2 = 0.11). The pattern of vari- ables was very similar to what is shown in Fig. 1. Hence, Table 3: OPLS regressions of PPT, CPT and HPT in women with CPP (n = 37). PPT – CPP women CPT– CPP women HPT– CPP women Variables VIP p(corr) Variables VIP p(corr) Variables VIP p(corr) PCS-rumination 1.45  −0.79 BMI 1.89 0.82 PSQ 1.96  −0.83 PSQ 1.41  −0.75 PSQ 1.76 0.77 BMI 1.83  −0.78 PCS-magnification 1.38  −0.74 PCS-rumination 1.19 0.52 PCS-rumination 1.01  −0.43 PCS-helplessness 1.14  −0.61 HADS-depression 0.82 0.36 Pain duration 0.79 0.34 HADS-depression 1.09  −0.58 Age 0.66 0.29 Age 0.70 −0.30 HADS-anxiety 0.92 −0.49 PCS-magnification 0.63 0.28 PCS-magnification 0.59 −0.25 BMI 0.79 −0.42 Pain duration 0.52 −0.23 HADS-depression 0.48 −0.21 Smoking 0.19 0.10 PCS-helplessness 0.31 0.14 PCS-helplessness 0.23 −0.10 Pain duration 0.14 0.08 HADS-anxiety 0.15 0.07 Smoking 0.17 −0.07 Age 0.10 −0.05 Smoking 0.09 0.04 HADS-anxiety 0.12 −0.05 R2 0.17 R2 0.52 R2 0.51 Q2 0.02 Q2 0.28 Q2 0.23 CV-ANOVA p-value 0.702 CV-ANOVA p-value 0.029 CV-ANOVA p-value 0.049 Number of subjects (n) 37 Number of subjects (n) 37 Number of subjects (n) 37 Variables with VIP > 1.0 and absolute p(corr) > 0.50 are significant and shown in bold type. The sign of p(corr) indicates the direction of the correlation with the dependent variable (+ = positive correlation;  −   = negative correlation). The four bottom rows of each regression report R 2, Q2, p-value of the CV-ANOVA and number of subjects (n). PPT = mean value of pressure pain thresholds; CPT = mean value of cold pain thresholds; HPT = mean value of heat pain thresholds; BMI = body mass index; Smoking = currently smoking (i.e. dummy variable: smoking = 1, non-smoking = 0); HADS = Hospital anxiety and depression scale; HADS-Depression = depression scale of HADS; HADS-anxiety = anxiety scale of HADS; Pain duration = pain duration in months; PCS = Pain Catastrophizing Scale; PCS-helplessness = helplessness scale of PCS; PCS-rumination = rumination scale of PCS; PCS- magnification = magnification scale of PCS; PSQ = Pain Sensitivity questionnaire – total index. 640 Grundström et al.: Pain catastrophizing is associated with pain thresholds in CPP the two HADS scales and the three PCS scales were highly intercorrelated (positively, i.e. they had the same sign and had high absolute p-values according to p1). The PSQ had a relatively high absolute loading on p1 but was more distant to the six psychological variables (not so strongly correlated with them). Smoking, BMI, and age –0.5 PCS_helpless PCS_magnif HADS_Anx Pain_dur HADS_Depr Smoking PSQ BMI Age PCS_rumin –0.5 –0.4 –0.3 –0.2 –0.1 0 0.1 0.2 0.3 –0.4 –0.3 –0.2 –0.1 p[1] p[2] 0 0.1 Fig. 2: PCA of the independent variables (X-variables) used in the regression of pain thresholds (cf. Table 3) in CPP (n = 37). Note that the second component p2 was not significant (only shown in order to improve interpretation). BMI = body mass index; Smoking = currently smoking (i.e. dummy variable: smoking = 1, non-smoking = 0); HADS-Depr = Hospital Anxiety and Depression Scale -depression scale; HADS-Anx = anxiety scale of HADS; Pain dur = pain duration; PCS = Pain Catastrophizing Scale; PCS-helpless = helplessness scale of PCS; PCS-rumin = rumination scale of PCS; PCS-magnif = magnification scale of PCS; PSQ = Pain Sensitivity questionnaire – total index. –0.5 PCS_helpless PCS_magnif HADS_Anx HADS_Depr Smoking PSQ BMI Age PCS_rumin –0.6 –0.4 –0.2 0 0.2 0.4 0.6 –0.4 –0.3 –0.2 –0.1 p[1] p[2] 0 0.1 0.2 Fig. 1: PCA of the independent variables (X-variables) used in the regression of pain thresholds (cf. Table 2) in all subjects taken together (n = 92). Note that the second component p2 was not significant (only shown in order to improve interpretation). BMI = body mass index; Smoking = currently smoking (i.e. dummy variable: smoking = 1, non-smoking = 0); HADS-Depr = Hospital Anxiety and Depression Scale; =depression scale of HADS; HADS-Anx = anxiety scale of HADS; PCS = Pain Catastrophizing Scale; PCS-helpless = helplessness scale of PCS; PCS-rumin = rumination scale of PCS; PCS-magnif = magnification scale of PCS; PSQ = Pain Sensitivity questionnaire – total index Grundström et al.: Pain catastrophizing is associated with pain thresholds 641 had low absolute loadings (<0.15) upon p1. Note that the second component p2 is only shown to improve interpreta- tion. It was not possible to obtain a significant PCA in the control group of healthy women. In Supplementary Figure S2 the three pain thresholds are included in the PCA. To summarise both the analysis of all subjects and the separate analysis of the CPP group (Figs. 1 and 2) showed that scales of HADS and PCS were strongly intercorrelated and that PSQ correlated positively with these variables. Hence, we found no evidence that the regressors in Tables 2 and 3 represented several groups of variables. 3.3 Relative importance of psychological variables and pain thresholds for group differentiating Group membership (y-variable) was regressed using the background variables, psychological variables, sub - jective pain sensitivity (PSQ) and pain thresholds as regressors (x-variables). From this significant OPLS-DA (Table 4) it can be concluded that the subscales of PCS and HADS were somewhat stronger regressors according to VIP and p(corr) than the three pain thresholds. PSQ, age, smoking and BMI were not significant regressors in this context (i.e. VIP <  1.0). Hence, the psychological variables contributed somewhat better than the pain thresholds to differentiating between CPP and healthy pain-free controls. This conclusion was further demonstrated in two additional analyses. When only including the psychologi- cal variables including PSQ together with the background variables, a model with higher explained variation was achieved compared to when the pain thresholds together with background data and PSQ were used as regressors of group membership (R 2 = 0.62, Q2 = 0.60, CV-ANOVA p-value < 0.001 versus R 2 = 0.43, Q2 = 0.40, CV-ANOVA p-value < 0.001). Hence, these two analyses confirm the

that the psychological variables were some- what more important than pain thresholds for group differentiation. 4 Discussion 4.1 Summary of findings Important results of the present study were: – Women with CPP reported more catastrophizing than healthy pain-free women. – In all subjects taken together, the three regressions of the pain thresholds had in common that PCS-help - lessness, PCS-rumination and HADS-depression were significant regressors. – In the group of women with CPP , the rumination sub- scale of PCS, BMI, and PSQ were significantly associ- ated with HPT and CPT. – The subscales of HADS and PCS were somewhat stronger regressors of group membership (control or CPP) than the three pain thresholds. Table 4: OPLS-DA of group membership (i.e. healthy control women denoted 0 and women with CPP denoted 1) using psychological variables, pain thresholds and background variables as regressors (x-variables). Variables VIP p(corr) PCS-helplessness 1.27 0.84 PCS-rumination 1.22 0.81 PCS-magnification 1.15 0.77 HADS-anxiety 1.15 0.76 HADS-depression 1.13 0.75 CPT 1.12 0.74 HPT 1.09 −0.72 PPT 1.07 −0.71 PSQ 0.92 0.61 Age 0.57 −0.38 Smoking 0.45 0.30 BMI 0.14 0.09 R2 0.64 Q2 0.62 CV-ANOVA p-value >0.001 Number of subjects (n) 92 Significant variables in bold type. Note that pain duration was not included in the regression since it defines the two groups of subjects. VIP (VIP > 1.0 is significant) and p(corr) are reported for each regressor. The sign of p(corr) indicates the direction of the correlation with the dependent variable (+ = positive correlation;  −   = negative correlation). The four bottom rows of each regression report R 2, Q2, and p-value of the CV-ANOVA and number of subjects included in the regression (n). PPT = mean value of pressure pain thresholds; CPT = mean value of cold pain thresholds; HPT = mean value of heat pain thresholds; BMI = body mass index; Smoking = currently smoking (i.e. dummy variable: smoking = 1, non-smoking = 0); HADS = Hospital anxiety and depression scale; HADS-Depression = depression scale of HADS; HADS-anxiety = anxiety scale of HADS; PCS = Pain Catastrophizing Scale; PCS-helplessness = helplessness scale of PCS; PCS-rumination = rumination scale of PCS; PCS- magnification = magnification scale of PCS; PSQ = Pain Sensitivity questionnaire – total index. 642 Grundström et al.: Pain catastrophizing is associated with pain thresholds 4.2 Interpretation of results in relation to current knowledge/literature Our results conform with previous studies proposing high pain catastrophizing in populations with chronic pain [12, 22–24, 26, 27 , 29, 30]. Catastrophizing is a significant variable for quality of life and treatment outcomes, where more catastrophizing leads to lower quality of life and less positive treatment outcomes. Furthermore, catastrophiz - ing is a predictor for poor outcome after surgery [39]. The relationships show the importance of taking catastrophiz- ing and other psychological aspects into account when treating people with chronic pain [24, 27 , 29]. Also, the regression of group membership (Table 4) showed that catastrophizing aspects together with other psychological aspects were associated with the clinical presentation in CPP . However, the relationships between catastrophizing and pain thresholds is somewhat different in the literature and in the present study. The OPLS regressions of CPT and HPT were signifi- cant, while the regression of PPT was not. The reasons for this need further evaluation. Meinits et al. [40] explored catastrophizing as a mediator for pain sensation in patients with chronic low back pain and found that PPT was inversely associated with pain catastrophizing [40]. Also, studies of chronic neck pain reported such a nega- tive association between PPT and catastrophizing [41, 42]. Partly in contrast, Walton et al. [43] analysed the pheno - types of individuals with neck pain in five international registers and found the association between PPTs and pain characteristics, including catastrophizing, to be con- flicting [43]. The psychological impact of the pain experience in CPP has been the focus of many studies, of which some are synthesised in the recent review by Till et  al. [25]. There is convincing evidence for the theory of pain and emotion regulation as a trans-diagnostic process [21], where anxiety, depression and catastrophizing are highly collinear and together may influence the pain experience, and vice versa [25]. Martinez-Calderon et al. [44] recently reported that the diagnosis of depression had a stronger association with pain hypersensitivity than pain catastro- phizing in patients with chronic shoulder pain [44]. In our results, the influence of PCS-rumination was significant for the regressions of the two thermal pain thresholds and a similar tendency was found in the non-significant regres- sion of PPT in the CPP group. The fact that PCS-rumination was consistently significant while depression and anxiety were not in the CPP group is interesting and indicates the important role of catastrophizing in the pain experience of CPP . The significance of the rumination scale of PCS may also suggest that rumination should be specifically targeted in the planning of new interventions. McPeak et al. [27] analysed the PCS subscales in relation to pain health-related quality of life. They found the strongest association between high helplessness and poor quality of life and suggested treatment strategies to manage pain catastrophizing [27]. The importance of taking a multi-dis- ciplinary approach and thereby including these types of psychological aspects in the treatment and care of women with CPP has frequently been highlighted in the literature [19, 23, 25]. This conclusion is further supported by the

of the present study where emotional stress (i.e. symptoms of depression and anxiety) and catastrophiz - ing aspects were increased in CPP and also constituted significant regressors for group membership. In order to understand the influence of psychological variables on the development of CPP , it may also be important to include pain catastrophizing. Previous studies have shown an age-dependent factor in pain catastrophizing, where younger age was associ- ated with higher pain catastrophizing intensity [22, 26]. We failed to demonstrate a significant age-dependent impact on pain catastrophizing. In contrast, BMI was a significant regressor for the two thermal pain thresholds but not for the pressure threshold. The scanty research on the influence of BMI upon pain sensitivity in women with CPP is ambiguous. Yosef et al. [29] found a positive association between high pain sensitivity and high BMI [29] while Gurian et al. [45] found higher pain thresholds among women with overweight compared with those with normal weight or with obesity [45]. This indicates that the influence of BMI upon pain thresholds merits further research. The data pinpoints that the psychological variables i.e. symptoms of anxiety and depression and the three aspects of catastrophizing together with the three pain thresholds significantly explained group membership. Hence, both the psychological variables and the pain thresholds con- tribute to the understanding of the clinical presentation. Moreover, the five psychological variables were – accord - ing to VIP and p(corr) – somewhat more important than the three pain thresholds even though the three latter variables were also significant. From a clinical perspec - tive, this information may be important since registration of pain thresholds is associated with short periods of pain and, moreover, is also considerably more time-consum- ing than filling out questionnaires on HADS and PCS. As Grundström et al.: Pain catastrophizing is associated with pain thresholds 643 reported by us previously, PSQ is associated with the three pain thresholds and higher in women with CPP [16] but in the present study with a relatively comprehensive set up of variables, it can be concluded that PSQ was not significant in the regression (OPLS-DA) of group membership. PSQ captures the overall perceived pain sensitivity while the pain thresholds – semi-objective measures – capture both stimuli specific information (mechanical pressure, cold or heat) and the degree of spatial spreading [10]. 4.3 Strengths and limitations A strength of this study was the use of validated instruments and methods that provided information on different aspects of the subject. All women with pain had experienced pelvic pain for at least 4  months, a period which is often set as the minimum for considering the pain as chronic [46]. Another strength was the use of MVDA, which is designed to use the properties of the data set in an optimal way. This approach differs from classical statistical methods, such as multiple linear regression, which have a tendency to quantify the level of relations of individual factors and at the same time disregard interrelationships among differ - ent factors [47]. We also avoided the use of multiple linear regression due to the risk of multicollinearity problems in our data set. Although parity differed significantly between the groups it was not possible to include this variable in the MVDA since it did not fulfil the predetermined criteria (i.e. it had a VIP value with a 95% jack-knife uncertainty confi- dence interval including zero). Even though the number of participants in the study was sufficient to enable PCA and OPLS, the sample size may be considered small and thus may be a limitation of the study. Due to the very few studies published on the subject and consequently the lack of reli- able information in the literature, no power analysis with sample size estimation was performed when planning the study. The sample size was intended to be at least the same as the studies previously published in the field. Another

may be that the women filled in the PCS after the QST, which may have influenced their scoring, even though the results of the QST were not disclosed. The cross-sec - tional design of the study and thus the direction of causal- ity between catastrophizing and pain thresholds cannot be analysed. The relationship may be bidirectional. 5 Conclusions This study showed that women with CPP , when measured by PCS, were more prone to exhibiting catastrophizing compared with healthy pain-free women. This was par - ticularly evident in regard to the PCS subscale ‘rumina- tion’ in the women with CPP . Although the pain thresholds (PPT, CPT and HPT) were all significantly associated with the PCS and HADS subscales they were weaker regressors of group membership. This underlines the importance of taking patients’ psychological status and coping strate- gies, such as catastrophizing, into consideration when analysing the occurrence of pain hypersensitivity as a proxy for nociplastic pain in women with CPP . Acknowledgments: The authors would like to thank all the participating women, and the research nurses for practical assistance in conducting the study. Authors’ statements Research funding: The study was supported financially with grants from the Medical Research Council of South- east Sweden, the Swedish Research Council, the County council of Östergötland, and Linköping University. L. Arendt-Nielsen was supported by IMI Paincare. Conflict of interest: The authors state no conflict of interest. Informed consent: Informed consent has been obtained from all participants included in this study. Ethical approval: The research related to human use com- plies with all the relevant national regulations, institu - tional policies and was performed in accordance with the tenets of the Helsinki Declaration, and has been approved by the Regional Ethics Board of Linkoping University (Reg. no. 2013/19-3).

[1] Ayorinde AA, Macfarlane GJ, Saraswat L, Bhattacharya SL. Chronic pelvic pain in women: an epidemiological perspective. Womens Health (Lond Engl) 2015;11:851–64. [2] Kobayashi H, Yamada Y, Morioka S, Niiro E, Shigemitsu A IF. Mechanism of pain generation for endometriosis-associated pelvic pain. Arch Gynecol Obs 2014;289:13–21. [3] Woolf CJ. Central sensitization: implications for the diagnosis and treatment of pain. Pain 2011;152:S2–S15. [4] Pavlaković G, Petzke F. The role of quantitative sensory testing in the evaluation of musculoskeletal pain conditions. Curr Rheu- matol Rep 2010;12:455–61. [5] Bajaj P , Bajaj P , Madsen H, Arendt-Nielsen L. Endometriosis is associated with central sensitization: a psychophysical con- trolled study. J Pain 2003;4:372–80. [6] Laursen BS, Bajaj P , Olesen AS, Delmar C, Arendt-Nielsen L. Health related quality of life and quantitative pain measure- ment in females with chronic non-malignant pain. Eur J Pain 2005;9:267–75. 644 Grundström et al.: Pain catastrophizing is associated with pain thresholds [7] He W, Liu X, Zhang Y, Guo SW. Generalized hyperalgesia in women with endometriosis and its resolution following a suc- cessful surgery. Reprod Sci 2010;17:1099–111. [8] As-Sanie S, Harris RE, Harte SE, Tu FF, Neshewat G, Clauw DJ. Increased pressure pain sensitivity in women with chronic pelvic pain. Obstet Gynecol 2013;122:1047–55. [9] Stratton P , Khachikyan I, Sinaii N, Ortiz R, Shah J. Associa- tion of chronic pelvic pain and endometriosis with signs of sensitization and myofascial pain. Obstet Gynecol 2015;125: 719–28. [10] Grundström H, Gerdle B, Alehagen S, Berterö C, Arendt-Nielsen L, Kjølhede P . Reduced pain thresholds and signs of sensiti- zation in women with persistent pelvic pain and suspected endometriosis. Acta Obstet Gynecol Scand 2019;98:327–36. [11] International Association of the Study of Pain. IASP Terminol- ogy. Avaiable at: https:/ /www.iasp-pain.org/Education/Con- tent.aspx?ItemNumber=1698. Accessed: 26 Dec 2019. [12] Edwards RR, Dworkin RH, Sullivan MD, Turk DC, Wasan AD. The role of psychosocial processes in the development and mainte- nance of chronic pain. J Pain 2016;17:T70–92. [13] Bär KJ, Brehm S, Boettger MK, Boettger S, Wagner G, Sauer H. Pain perception in major depression depends on pain modal- ity. Pain 2005;117:97–103. [14] Ruscheweyh R1, Marziniak M, Stumpenhorst F, Reinholz J KS. Pain sensitivity can be assessed by self-rating: development and validation of the Pain Sensitivity Questionnaire. Pain 2009;146:64–74. [15] Schwier C, Kliem A, Boettger MK, Bär KJ. Increased cold-pain thresholds in major depression. J Pain 2010;11:287–90. [16] Grundström H, Larsson B, Arendt-Nielsen L, Gerdle B, Kjølhede P . Associations between pain thresholds for heat, cold and pressure, and Pain Sensitivity Questionnaire scores in healthy women and in women with persistent pelvic pain. Eur J Pain 2019;23:1631–9. [17] Aldao A, Nolen-Hoeksema S. Specificity of cognitive emotion regulation strategies: a transdiagnostic examination. Behav Res Ther 2010;48:974–83. [18] Paulus DJ, Bakhshaie J, Garza M, Ochoa-Perez M, Mayorga NA, Bogiaizian D, Robles Z, Lu Q, Ditre J, Vowles K, Schmidt NB, Zvolensky MJ. Pain severity and emotion dysregulation among Latinos in a community health care setting: relations to mental health. Gen Hosp Psychiatry 2016;42:41–8. [19] Linton SJ, Bergbom S. Understanding the link between depres- sion and pain. Scand J pain 2011;2:47–54. [20] Svanberg M, Stålnacke BM, Enthoven P , Brodda-Jansen G, Gerdle B, Boersma K. Impact of emotional distress and pain- related fear on patients with chronic pain: subgroup analysis of patients referred to multimodal rehabilitation. J Rehabil Med 2017;49:354–61. [21] Linton SJ. A transdiagnostic approach to pain and emotion. J Appl Biobehav Res 2013;18:82–103. [22] Leung L. Pain catastrophizing: an updated review. Indian J Psychol Med 2012;34:204–17. [23] Bryant C, Cockburn R, Plante AF, Chia A. The psychological profile of women presenting to a multidisciplinary clinic for chronic pelvic pain: high levels of psychological dysfunction and implications for practice. J Pain Res 2016;9:1049–56. [24] Sewell M, Churilov L, Mooney S, Ma T, Maher P , Grover SR. Chronic pelvic pain – pain catastrophizing, pelvic pain and quality of life. Scand J Pain 2018;18:441–8. [25] Till S, As-Sanie S, Schrepf A. Psychology of chronic pelvic pain. Clin Obstet Gynecol 2019;62:22–36. [26] Martin CE, Johnson E, Wechter ME, Leserman J, Zolnoun DA. Catastrophizing: a predictor of persistent pain among women with endometriosis at 1 year. Hum Reprod 2011;26:3078–84. [27] McPeak AE, Allaire C, Williams C, Albert A, Lisonkova S, Yong PJ. Pain catastrophizing and pain health-related quality-of-life in endometriosis. Clin J Pain 2018;34;349–56. [28] Payne LA, Rapkin AJ, Lung KC, Seidman LC, Zeltzer LK, Tsao JC. Pain catastrophizing predicts menstrual pain ratings in adoles- cent girls with chronic pain. Pain Med 2016;17:16–24. [29] Yosef A, Allaire C, Williams C, Ahmed AG, Al-Hussaini T, Abdel- lah MS, Wong F, Lisonkova S, Yong PJ. Multifactorial contribu- tors to the severity of chronic pelvic pain in women. Am J Obstet Gynecol 2016;215:760.e1–14. [30] Rivest K, Côté JN, Dumas JP , Sterling M, De Serres SJ. Relation- ships between pain thresholds, catastrophizing and gender in acute whiplash injury. Man Ther 2010;15:154–9. [31] Sullivan MJL, Bishop SR, Pivik J. The Pain Catastrophizing Scale: development and validation: EBSCOhost. Psychol Assess 1995;7:524–32. [32] Karlsson CLK. Swedish validation of Pain Catastrophizing Scale [In Swedish: Svensk validering av Pain Catastrophizing Scale samt sambanden mellan smärtkatastrofiering, sömnproblem och ångest respektive depression 2018] Avaiable at: http:/ / www.diva-portal.org/smash/record.jsf?pid=diva2%3A1188911 &dswid=9314. Accessed:23 September 2019. [33] Zigmond AS, Snaith RP . The hospital anxiety and depression scale. Acta Psychiatr Scand 1983;67:361–70. [34] Lisspers J, Nygren A, Söderman E. Hospital Anxiety and Depres- sion Scale (HAD): some psychometric data for a Swedish sample. Acta Psychiatr Scand 1997;96:281–6. [35] Mücke M, Cuhls H, Radbruch L, Baron R, Maier C, Tölle T, Treede RD, Rolke R. Quantitative sensory testing (QST). Schmerz 2016;1–8. DOI: 10.1007/s00482-015-0093-2. [36] Rolke R, Magerl W, Campbell KA, Schalber C, Caspari S, Birklein F, Treede RD. Quantitative sensory testing: a comprehensive protocol for clinical trials. Eur J Pain 2006;10:77–88. [37] Wheelock ÅM, Wheelock CE. Trials and tribulations of’ omics data analysis: assessing quality of SIMCA-based multivariate models using examples from pulmonary medicine. Mol Biosyst 2013;9:2589–96. [38] Eriksson L, Johansson E, Kettaneh-Wold N, Trygg J, Wikström C, Wold S. Multi- and megavariate data analysis; part I and II. Umeå: Umetrics AB, 2006. [39] Khan RS, Ahmed K, Blakeway E, Skapinakis P , Nihoyannop- oulos L, Macleod K, Sevdalis N, Ashrafian H, Platt M, Darzi A, Athanasiou T. Catastrophizing: a predictive factor for postop- erative pain. Am J Surg 2011;201:122–31. [40] Meints SM, Mawla I, Napadow V, Kong J, Gerber J, Chan ST, Wasan AD, Kaptchuk TJ, McDonnell C, Carriere J, Rosen B, Gol- lub RL, Edwards RR. The relationship between catastrophizing and altered pain sensitivity in patients with chronic low-back pain. Pain 2019;160:833–43. [41] Muñoz-García D, López-de-Uralde-Villanueva I, Beltrán- Alacreu H, La Touche R, Fernández-Carnero J. Patients with concomitant chronic neck pain and myofascial pain in masticatory muscles have more widespread pain and distal hyperalgesia than patients with only chronic neck pain. Pain Med 2017;18:526–37. Grundström et al.: Pain catastrophizing is associated with pain thresholds 645 [42] Sá S, Silva AG. Repositioning error, pressure pain threshold, catastrophizing and anxiety in adolescents with chronic idi- opathic neck pain. Musculoskelet Sci Pract 2017;30:18–24. [43] Walton DM, Kwok TS, Mehta S, Loh E, Smith A, Elliott J, Kamper SJ, Kasch H, Sterling M. Cluster analysis of an international pressure pain threshold database identifies 4 meaningful subgroups of adults with mechanical neck pain. Clin J Pain 2017;33:422–8. [44] Martinez-Calderon J, Meeus M, Struyf F, Diaz-Cerrillo JL, Clavero-Cano S, Morales-Asencio JM, Luque-Suarez A. Psy- chological factors are associated with local and generalized pressure pain hypersensitivity, pain intensity, and function in people with chronic shoulder pain: a cross-sectional study. Musculoskelet Sci Pract 2019;44:102064. [45] Gurian MB, Mitidieri AM, da Silva JB, da Silva AP , Pazin C, Poli- Neto OB, Nogueira AA, dos Reis FJ, Rosa-Silva JC. Measurement of pain and anthropometric parameters in women with chronic pelvic pain. J Eval Clin Pract 2015;21:21–7. [46] International Association for the Study of Pain. Classification of chronic pain: descriptions of chronic pain syndromes and definitions of pain terms. Washington: IASP Press, 1994. [47] Jansen JJ, Szymańska E, Hoefsloot HC, Jacobs DM, Strassburg K, Smilde AK. Between metabolite relationships: an essential aspect of metabolic change. Metabolomics 2012;8:422–32. Supplementary Material: The online version of this article offers supplementary material (https:/ /doi.org/10.1515/sjpain-2020-0015). 646 Grundström et al.: Pain catastrophizing is associated with pain thresholds