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. 2021 Nov 20;74(3):267–275. doi: 10.3138/ptc-2020-0093

Factors Associated with Intermittent, Constant, and Mixed Pain in People with Knee Osteoarthritis

Fatme Hoteit *, Debbie Erhmann Feldman †,‡, Lisa C Carlesso §,¶,**
PMCID: PMC10262826  PMID: 37325210

Abstract

Purpose: To explore factors associated with intermittent, constant, and mixed pain in people with knee osteoarthritis. Method: We conducted a secondary analysis of a cross-sectional multicentre study with adults ≥ 40 years with knee osteoarthritis. Participants completed questionnaires on personal (e.g., demographics, comorbidities), physical (e.g., physical function), psychological (e.g., depressive symptoms), pain (e.g., qualities), and tests for physical performance and nervous system sensitivity. We qualified patients’ pain as intermittent, constant, or mixed using the Modified painDETECT Questionnaire and assessed associations with the variables using multinomial logistic regression. Results: The 279 participants had an average age of 63.8 years (SD 9.6), BMI of 31.5 kg/m2 (SD 8.7), and 58.6% were female. Older age (odds ratio [OR] 0.95; 95% CI: 0.90, 1.00) and higher self-reported physical function (OR 0.94; 95% CI: 0.91, 0.98) were associated with a lower likelihood of mixed pain compared with intermittent pain. Higher pain intensity (OR 1.25; 95% CI: 1.07, 1.47) was related to a 25% higher likelihood of mixed pain compared with intermittent pain. Conclusions: This study provides initial data for associations of personal, pain, and physical function factors with different pain patterns. Awareness of these factors can help clinicians develop targeted strategies for managing patients’ pain.

Key Words: acute pain, chronic pain, knee osteoarthritis, pain measurements, risk factors

Osteoarthritis (OA) is a serious chronic disease ranked as the 12th leading cause of years lived with disability globally due to its accompanying pain and reduction in function.1 OA is a major contributor to disability in Canada; it affects 13% of Canadian adults, and approximately 400,000 are newly diagnosed each year.2 By the year 2040, an estimated one in four Canadians will have OA, leading to a 46% increase in health care costs due to loss of work productivity.3 Knee OA is the most prevalent form.4

Pain is the main hallmark of OA, and understanding pain in knee OA is particularly complex. The frequency and severity of pain associated with knee OA increase with progression of the disease5 and present in three patterns: intermittent, constant, and mixed.6 Intermittent pain typically starts at an early stage of the disease, and patients describe it as pain that is sharp, comes and goes, and is triggered by high-impact activities involving the knee. Patients describe constant pain, which occurs at later stages, as dull, aching, and predictable; as being there all the time; and as leading to limitations in daily activities.7 Finally, mixed pain appears at the end stage of the disease; patients experience a combination of constant pain and intermittent flares of high-intensity pain. Evidence supports the association of these pain patterns with the duration and severity of knee OA.6

The experience of pain is multidimensional, influenced by personal (e.g., sex, BMI, comorbidities), physical (e.g., sleep, fatigue, physical function), and psychological (e.g., anxiety and depressive symptoms, catastrophizing) factors. However, little research has addressed whether each of these factors is associated with the intermittent, constant, and mixed pain patterns. In addition, no research has quantified details on the nature of the pain, such as peripheral or central nervous system sensitization, neuropathic pain, widespread pain (WSP), or variability. Previous studies found nervous system sensitization to nociceptive signaling, neuropathic pain, and WSP in people with knee OA8–10 but did not report their associations with the pain patterns. Similarly, existing research on the variability of pain has provided only qualitative descriptions.7

The associations of these factors with the three pain patterns may provide evidence about the transition from intermittent to constant and to mixed pain and may shed light on the reasons not everyone experiences these transitions. The objective of this study was to explore the associations of the three pain patterns with personal, physical, psychological, pain, and nervous system factors in patients with knee OA.

Methods

Participants

For this secondary cross-sectional analysis of a prospective, multi-centre study, we recruited participants from three university hospital centres in Montreal, Quebec, between May 2017 and May 2019. We identified eligible participants after their initial consultation with an orthopaedic surgeon; we included those aged 40 years and older with a confirmed diagnosis of knee OA meeting the radiographic and clinical criteria of the American College of Rheumatology.11 We excluded potential participants who had inflammatory arthritis, major knee trauma in the previous year, a history of knee surgery, severe heart disease, or impaired cognition or who were not fluent in either English or French.

The research ethics board of the Centre intégré universitaire de santé et de services sociaux de l’Est-de-l’Île-de-Montréal approved the protocol, and we conducted the study in accordance with the ethical standards set forth in the 1964 Declaration of Helsinki and its later amendments. We read and explained the information and consent form to all participants, and all participants signed the form.

Data collection

We collected data in two phases. In the first phase, participants completed a suite of questionnaires on personal, physical, psychological, and pain characteristics. The second phase occurred within 2 to 4 weeks of consent and consisted of onsite physical performance and psychophysical (nervous system) testing. In the sections that follow, we briefly describe the variables and measurement tools used.

Phase 1 – Questionnaires

Personal factors: Participants reported their age, sex, weight, height, education level, ethnic origin, marital status, and income level in response to questions based on the 1998 Quebec Health Survey.12 We calculated BMI using patient-reported weight and height. One senior orthopaedic surgeon assessed the participants’ Kellgren and Lawrence grade, a rating of OA severity, on an anteroposterior x-ray.13 Participants reported comorbidities on the self-report version of the Charlson Comorbidity Index.14

Physical factors: Participants reported their sleep quality using the Pittsburgh Sleep Quality Index15 and their fatigue using the Multidimensional Fatigue Inventory.16 They self-reported their physical function using the Knee Injury and Osteoarthritis Outcomes Score (KOOS) Activities of Daily Living subscale, previously validated in patients with knee OA.17

Psychological factors: Participants completed the Hospital Anxiety and Depression Scale18 as a measure of anxiety and depressive symptoms, the Patient Health Questionnaire–1519 as a measure of somatization, the Pain Catastrophizing Scale20 as a measure of catastrophizing, and the Life Orientation Test–Revised21 as a measure of optimism. They also completed the Chronic Pain Self-Efficacy Scale.22

Pain factors: Participants characterized the qualities of their pain with the Short-Form McGill Pain Questionnaire–2,23 on which they rate 22 pain descriptors from none to worst possible, and their neuropathic pain using the Modified painDETECT Questionnaire (mPDQ).24 We calculated widespread pain from participants’ indications on a body homunculus using a previously validated definition.25 We measured pain variability using the average of the standard deviation of three pain intensity ratings per day for 1 week, as previously recommended.26 We collected the pain intensity ratings by sending participants automated texts or voice messages asking them to rate their current pain intensity on the 0–10 numeric pain rating scale.27

Phase 2 – Physical performance and psychophysical testing

All tests were conducted by a trained research assistant who was also a practicing physiotherapist.

Physical performance tests: We used three main core tests the Osteoarthritis Research Society International28 as recommended for assessing lower limb strength and balance: the 30-second chair stand test, the 40-metre fast walk test, and the stair climb test.

The 30-second chair stand test measures sit-to-stand ability as an indication of lower extremity strength and balance. Participants crossed their arms at the wrist and held them close to the chest as they sat in a chair with a seat 43.2 centimetres (17 in.) We instructed them to sit and stand repeatedly as fast as possible and recorded the number of repetitions done in 30 seconds.

The 40-metre fast walk test assesses short-distance walking ability, walk speed, and ability to change direction. We instructed participants to walk quickly but safely four times around two cones set 10 meters apart, staying within 2 meters of the cones while turning. For the stair climb test, we instructed participants to climb and descend nine steps with a height of 23.3 centimetres (8 in.). For the walking and climbing tests, we measured time with a handheld stopwatch and recorded results to the 10th of a second.

Psychophysical (nervous system) tests: We evaluated nervous system sensitization with several psychophysical tests: temporal summation (TS), pressure pain threshold (PPT), heat and cold pain threshold (HPT, CPT), and conditioned pain modulation (CPM). We administered all tests at the index knee at the patella and the opposite volar forearm.

We evaluated TS mechanically using a weighted Von Frey monofilament (Bioseb In Vivo Research Instruments) (60 g) to the forearm. After we applied four stimuli,29 participants rated their pain between 0 and 100. Next, we applied the stimulus 30 times at the frequency of one per second and participants rated their pain again.30 TS is the difference between the first rating and the last.31 The test-retest reliability of TS in people with knee OA is very good at superficial and deep tissues; reported intra-class correlation coefficients (ICCs) are 0.79–0.82.32

We assessed PPT by applying an electronic digital pressure algometer (1-cm2 rubber tip; Wagner FDIX 25, Wagner Instruments, Greenwich, CT) to the forearm and patella at a rate of 0.5 kilograms per second until participants reported that the sensation changed to a painful one. We used the average score from three trials for the analysis.29 Standard error of measurement of PPT in painful knee OA was reported to be 0.70–0.66 with high reliability (test–retest) of 0.83–0.98.33

We tested HPT and CPT using a Peltier 3 cm × 3 cm thermode (Medoc TSA-II NeuroSensory Analyzer, Ramat Yishay, Israel). At a rate of 1 degree Celsius per second, we applied cold to a minimum of 0 degrees and heat to a maximum of 50 degrees34 until participants indicated a painful heat or cold sensation. We used the average score from three trials at each site for the analysis.34 Reported reliability values (ICCs) for patients with knee OA are 0.70 for CPT at the patella, 0.41 for CPT at the forearm, 0.77 for HPT at the patella, and 0.86 for HPT at the forearm.34

We evaluated CPM using PPT or HPT as the test stimulus and CPT as the conditioning stimulus. For PPT, we first applied increasing pressure to the painful patella until the participant noted a verbal pain rating of 4 out of 10. Next, we applied cold to the opposite forearm to a pain rating of 6 out of 10 maintained for 1 minute. Finally, we assessed PPT in the patella a second time.35 For HPT, we repeated this process with heat as the test stimulus, applied to the index patella at a rate of 1 degree per second (to a maximum of 50 degrees) until the participant reported a verbal pain rating of 4 out of 10. We subtracted the first PPT and HPT values from the second; negative values demonstrate pain facilitation and positive values show pain inhibition.35,36 CPM testing has good test-retest reliability, with reported ICCs of 0.75–0.85.36

Dependent variable – Intermittent, constant, and mixed pain

We used the image in Figure 1 from the Modified pain-DETECT Questionnaire to categorize participants as having intermittent, constant, or mixed pain. We instructed participants to choose the graph that best described the course of their pain. We categorized patients who chose graph 3 as having intermittent pain – attacks with no pain between them – and those who chose graph 1 as having constant pain – persistent pain with slight fluctuations. We categorized patients who chose graph 2 or 4 as having mixed pain – persistent pain with intermittent pain attacks.

Figure 1 .

Figure 1

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Images from the mPDQ categorizing participants with intermittent (image 3), constant (image 1) or mixed pain (intermittent + constant pain, images 2 and 4).

Analyses

We described the sample using means and standard deviations for continuous variables and frequencies and proportions for dichotomous variables. We categorized the independent variables as follows: personal (age, sex, BMI, education level, ethnic origin, marital status, income level, Kellgren and Lawrence grade, and comorbidities), physical (sleep, fatigue, self-reported physical function, 30-s chair stand test, 40-m fast walk test, and stair climb test), psychological (anxiety and depressive symptoms, somatization, catastrophizing, optimism, and pain self-efficacy), pain (qualities, neuropathic pain, widespread pain, variability, and intensity), and nervous system (TS, PPT, HPT, CPT, and CPM).

We examined multicollinearity to identify independent variables with a correlation of greater than 0.70. We next assessed the association of each of the variables in each category separately with our dependent variable of interest using multinomial logistic regression. The dependent variable was pain pattern with three categories (intermittent, constant, and mixed pain); the independent variables were each of the factors in the personal, physical, psychological, pain, and nervous system categories.

We retained variables with a significance of p < 0.20,37 for the final model and ran the final model with all remaining variables entered simultaneously. We assessed model fit using the deviance and log likelihood tests and calculated odds ratios (ORs) with intermittent pain as the reference pattern. We performed all analyses using IBM SPSS Statistics (Version 25; IBM Corporation, Armonk, NY).

Results

Our sample consisted of 297 participants; 58.6% (174) were female, average age was 63.8 years (SD 9.6), and average BMI was 31.5 kg/m2 (SD 8.7). Regarding the pain patterns, 35.7% (106) of participants had intermittent pain, 20.9% (62) had constant pain, and 43.4% (129) had mixed pain. Table 1 presents descriptive characteristics for participants’ personal, physical, psychological, pain, and nervous system factors.

Table 1 .

Participants’ Personal, Physical, Psychological, Pain, and Nervous System Characteristics

Characteristics Mean (SD)*
All patterns (N = 297) Intermittent pattern (n = 106) Constant pattern (n = 62) Mixed pattern (n = 129)
Personal factors
 Age, y 63.8 (9.6) 65.6 (9.7) 65.1 (9.3) 61.6 (9.2)
 Sex (female), no. (%) 174 (58.6) 65 (61.3) 22 (35.5) 87 (67.4)
 BMI 31.5 (8.7) 30.6 (8.8) 29.8 (4.6) 33.1 (9.8)
 Education level, high school or less, no. (%) 104 (35.0) 29 (27.4) 26 (41.9) 49 (38.0)
 Ethnic origin, Caucasian, no. (%) 261 (87.9) 91 (85.8) 55 (88.7) 115 (89.1)
 Marital status, single, no. (%) 124 (41.8) 51 (48.1) 30 (48.4) 43 (33.3)
 Income level, ≤ $49,999, no. (%) 115 (38.7) 33 (31.1) 27 (43.5) 55 (42.6)
 Kellgren and Lawrence grade (OA severity), ≥2, no. (%) 182 (61.3) 69 (65.1) 36 (58.1) 77 (59.7)
 Charlson Comorbidity Index score: /37 (higher scores indicate greater comorbidity) 0.7 (1.7) 0.6 (1.5) 0.6 (1.7) 0.8 (1.9)
Physical factors
 Pittsburgh Sleep Quality Index score: /21 (higher scores indicate greater severity) 7.3 (4.4) 6.6 (4.3) 7.5 (4.3) 7.7 (4.6)
 Multidimensional Fatigue Inventory score: /100 (higher scores indicate greater severity) 52.5 (14.6) 50.1 (14.3) 48.9 (14.4) 56.1 (14.1)
 Knee Injury and Osteoarthritis Outcomes Score, score ADL subscale /100 (higher scores indicate better physical function) 58.5 (19.8) 68.0 (19.5) 63.0 (16.9) 48.6 (16.7)
 30-s chair stand test, no. of repetitions (higher scores indicate better physical function) 10.4 (5.1) 11.2 (6.1) 10.6 (5.0) 9.7 (4.3)
 40-m fast walk test (higher scores indicate greater physical difficulties) 36.8 (11.9) 36.3 (12.8) 34.6 (10.1) 38.2 (11.8)
 Stair climb test (higher scores indicate greater physical difficulties) 15.4 (8.5) 14.9 (9.4) 13.8 (7.2) 16.5 (8.2)
Psychological factors
 Hospital Anxiety and Depression Scale, score: /42 (higher scores indicate greater severity) 9.9 (6.8) 8.8 (6.3) 9.1 (7.3) 11.2 (6.8)
 Patient Health Questionnaire–15 scores (somatization), score: /30 (higher scores indicate greater severity) 6.7 (4.5) 5.9 (4.1) 5.3 (4.6) 8.0 (4.4)
 Pain Catastrophizing Scale scores, score: /52 (higher scores indicate greater severity) 17.3 (13.1) 13.7 (11.0) 14.2 (12.4) 21.7 (13.6)
 Life Orientation Test–Revised scores (optimism), score: /40 (higher scores indicate greater optimism) 16.2 (4.1) 16.4 (4.0) 16.4 (3.6) 15.8 (4.3)
 Chronic Pain Self-Efficacy Scale, score: /60 (higher scores indicate greater self-efficacy) 38.9 (12.7) 40.4 (12.8) 40.9 (12.4) 36.6 (12.4)
Pain factors
 Short-Form McGill Pain Questionnaire–2 (pain qualities), score: /220 (higher scores indicate greater severity) 52.4 (43.4) 37.7 (38.4) 39.1 (33.6) 70.7 (44.7)
 Modified painDETECT Questionnaire (neuropathic pain), /38 (higher scores indicate greater NP) 11.8 (7.4) 9.6 (6.7) 9.9 (6.8) 14.5 (7.4)
 Widespread pain, yes, no. (%) 60 (20.2) 19 (17.9) 10 (16.1) 31 (24.0)
 Pain variability 12.7 (6.7) 12.1 (6.4) 9.9 (6.6) 14.4 (6.6)
 Pain intensity scores, score: /10 (10 indicates greater pain intensity) 4.2 (3.2) 3.0 (2.9) 3.0 (2.9) 5.8 (2.9)
Nervous system factors
 Temporal summation, forearm, difference in 2 pain ratings /100 10.4 (10.5) 9.1 (8.7) 10.3 (9.9) 11.7 (12.1)
 Temporal summation, patella, difference in 2 pain ratings /100 11.7 (11.8) 9.9 (10.3) 14.1 (13.3) 9.7 (10.1)
 Pressure pain threshold, forearm, kg/cm2 2.4 (1.0) 2.3 (1.1) 2.5 (1.1) 2.3 (1.0)
 Pressure pain threshold, patella, kg/cm2 4.2 (2.1) 4.4 (2.0) 4.8 (2.3) 3.8 (2.0)
 Heat pain threshold, forearm, °C 44.7 (4.7) 45.0 (4.4) 44.8 (5.1) 44.5 (4.6)
 Cold pain threshold, forearm, °C 12.1 (11.4) 10.9 (11.1) 12.5 (11.5) 12.8 (11.6)
 Heat pain threshold, patella, °C 47.4 (3.1) 47.5 (2.8) 47.6 (3.5) 47.1 (3.1)
 Cold pain threshold, patella, °C 8.3 (11.0) 6.9 (10.3) 8.8 (12.3) 9.2 (10.8)
 Conditioned pain modulation, heat pain threshold, pre–post change, °C −0.7 (1.7) −0.5 (1.6) −0.6 (1.3) −1.0 (1.9)
 Conditioned pain modulation, pressure pain threshold, pre–post change, kg/cm2 3.4 (7.8) 2.5 (9.3) 5.1 (7.7) 3.4 (6.2)
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*

Unless otherwise indicated.

Assessment for multicollinearity resulted in the removal of two variables (40-m fast walk test and stair climb test). After the initial model, we excluded 14 variables because of p-values greater than 0.20: BMI, education level, ethnic origin, income level, Kellgren and Lawrence grade, anxiety and depressive symptoms, optimism, self-efficacy, widespread pain, TS patella, HPT forearm, CPT forearm, HPT patella, and CPT patella. We thus retained 19 variables for the final model: age, sex, marital status, comorbidities, sleep, fatigue, self-reported physical function, 30-second chair stand test, somatization, catastrophizing, pain qualities, neuropathic pain, pain variability, pain intensity, TS forearm, PPT forearm, PPT patella, CPM for HPT, and CPM for PPT.

We found significant associations for age (p = 0.032), KOOS score (self-reported physical function), and pain intensity with having mixed pain compared with intermittent pain. Specifically, for every 1-year increase in age, a participant was 5% less likely, and for every 1-point increase in KOOS score, a participant was 6% less likely, to have mixed pain compared with intermittent pain. Increased pain intensity was associated with 25% greater odds of having mixed pain compared with intermittent pain (OR 1.25; 95% CI: 1.07, 1.47). In addition, women were 71% less likely than men to have constant pain compared with intermittent pain (OR 0.29; 95% CI: 0.11, 0.75; seeTable 2).

Table 2 .

Associations Between Pain Patterns and Personal, Physical, Psychosocial, Pain, and Nervous System Variables in the Final Model

Variables Intermittent (reference category) Pain pattern* OR (95% CI)
Constant Mixed
Age 1 1.00 (0.95, 1.04) 0.95 (0.90, 1.00)
Sex: female 1 0.29 (0.11, 0.75) 0.46 (0.18, 1.19)
Marital status: single 1 1.14 (0.47, 2.77) 0.60 (0.25, 1.40)
Comorbidities 1 0.87 (0.63, 1.20) 1.07 (0.83, 1.37)
Sleep 1 1.13 (0.99, 1.30) 0.90 (0.79, 1.01)
Fatigue 1 0.98 (0.94, 1.02) 1.00 (0.97, 1.04)
Self-reported physical function 1 0.99 (0.96, 1.02) 0.94 (0.91, 0.98)§
30-s chair stand test 1 0.95 (0.87, 1.05) 1.03 (0.94, 1.13)
Somatization 1 0.94 (0.83, 1.07) 1.05 (0.92, 1.18)
Catastrophizing 1 0.99 (0.94, 1.04) 1.02 (0.98, 1.06)
Pain qualities 1 1.00 (0.99, 1.02) 1.00 (0.98, 1.01)
Neuropathic pain 1 1.00 (0.93, 1.09) 1.01 (0.94, 1.08)
Pain variability 1 0.97 (0.90, 1.04) 1.05 (0.98, 1.12)
Pain intensity 1 1.07 (0.90, 1.27) 1.25 (1.07, 1.47)
TS forearm 1 1.02 (0.97, 1.07) 1.02 (0.97, 1.06)
PPT forearm 1 1.08 (0.65, 1.79) 1.02 (0.63, 1.66)
PPT patella 1 0.95 (0.74, 1.23) 0.83 (0.63, 1.11)
CPM for HPT 1 0.99 (0.75, 1.30) 0.94 (0.73, 1.21)
CPM for PPT 1 1.03 (0.97, 1.09) 1.02 (0.96, 1.07)
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*

With intermittent as the reference category.

OR = odds ratio; TS = temporal summation; CPM = conditioned pain modulation; HPT = heat pain test; PPT = pressure pain threshold.

Discussion

We explored the associations of factors known to represent the multidimensional nature of pain with intermittent, constant, and mixed pain patterns in people with knee OA. Our previous scoping review demonstrated that since the initial qualitative work describing these pain patterns, few studies have provided additional knowledge to enhance the understanding of these patterns.38 The results of the current study provide new information regarding the associations of personal (age, sex), physical (self-reported physical function), and pain (intensity) factors with the pain patterns. On average, participants with constant or mixed pain, compared with those with intermittent pain, were slightly younger, were more likely to be women, reported poorer physical function, and had higher levels of pain intensity. These results are in line with previous studies reporting the associations of pain and its multidimensional aspects with the progression of knee OA symptoms.39–41

Results from our sample show that a larger proportion of men reported constant pain, whereas the literature has established that women have higher rates of OA and chronic pain than men.42,43 Two other studies have specifically examined pain patterns and sex. Song et al.44 used the Intermittent and Constant Osteoarthritis Pain (ICOAP) questionnaire to identify intermittent and constant pain patterns (no pain, intermittent pain below and above median level, and constant pain ) and found that rates of intermittent and constant pain were slightly higher in women and consistent across categories of variables. In a women-only sample, Soni et al.45 defined pain patterns based on the frequency of pain reports over a 12-year period and reported higher rates of intermittent pain compared with constant pain. Soni et al. also showed natural variation in pain over this period, with approximately one-third of participants who had knee pain at baseline reporting having no knee pain at three follow-up time points. The divergent results for women in these two studies and our own may be due to differences in the definitions of the pain patterns. In addition, the three studies used three different methods of data collection. Comparing the results of future studies will be aided by the use of similar measures and procedures and the inclusion of both sexes.

We found an association between age and having mixed versus intermittent pain that was contrary to our expectation because OA tends to worsen with age both structurally and symptomatically.46 Although the association of age with constant versus intermittent pain was nonsignificant, the estimate was very similar to that for mixed versus intermittent pain, with both hovering around the null. It may be that with increasing age and progression of disease to a later stage, the transition to constant pain is a pivotal point after which age has little effect and further worsening of pain is related to joint failure. This association needs to be confirmed longitudinally.

We found that self-reported physical function as measured by the KOOS Activities of Daily Living subscale was significantly lower in participants with mixed pain, indicating poorer function. Our results complement those of a previous study using the ICOAP questionnaire in which a decrease in the KOOS Function in Sport and Recreation subscale score was associated with an increase in the ICOAP Intermittent Pain and Constant Pain subscale scores over 2 years in both men and women.47 Taken together, these findings demonstrate poorer function with higher severity of symptoms, as is typically experienced by people with mixed pain.7 Plus, previous studies assessing the associations of ICOAP scores with physical function and performance tests have shown that Intermittent Pain subscale scores are higher than Constant Pain subscale scores, however the study used different categories of pain patterns differently making it difficult to compare.47 These results should be analysed with caution as unlike our study, in which participants could indicate only one pain pattern, participants in the ICOAP studies might have completed both subscales, so it is unknown which pattern they had.

Another study used the ICOAP questionnaire to evaluate the association of pain patterns with time spent in physical activity as measured by an accelerometer.44 Using Osteoarthritis Initiative data, Song et al. categorized participants as having (1) no pain, (2) lower intermittent pain (no constant pain, Intermittent Pain score below the median), (3) higher intermittent pain (no constant pain, Intermittent Pain score above the median), and (4) constant pain with or without intermittent pain.44 Constant pain had a bigger impact on physical activity: participants with constant pain showed less light-intensity activity (2,024 min/wk) and moderate-intensity activity (46 min/wk) than those with lower intermittent pain (2,071 and 70 min/wk, respectively) and higher intermittent pain (2,111 and 53 min/wk, respectively). Unfortunately, results for participants in the constant pain group were not separated into those with and without intermittent pain. However, Intermittent Pain subscale scores in the constant pain group were only slightly less than in the higher intermittent pain group, demonstrating the severity of intermittent pain compared to constant. The Constant Pain subscale scores were also higher than the Intermittent Pain subscale scores for the higher intermittent pain group.44 Further longitudinal exploration of physical function and pain patterns is needed to help clarify these discrepancies in the literature.

Lastly, we found that participants with higher pain intensity were 25% more likely to have mixed pain than intermittent pain only. This result is in line with recent findings from the Multicenter Osteoarthritis Study (MOST), which used the ICOAP pain pattern categories; that study found higher pain severity in participants with mixed pain and a concordance with duration of radiographic OA.6 Results from the original development study for the ICOAP also support these findings.7 To our knowledge, no other study has examined the association of pain intensity with the pain patterns. Other studies have used only the subscale scores of the ICOAP, which go beyond pain intensity to provide a multidimensional representation of each construct. This tool includes questions about sleep, quality of life, and mood indicative of the overall burden related to each type of pain. Our use of the image from the Modified painDETECT Questionnaire (Figure 1) to categorize the pain patterns was independent of our measure of pain intensity (the 0–10 numeric pain rating scale). The similarity in results regarding pain intensity and the pain patterns between our participants and the MOST cohort suggests that the graphs in the mPDQ image and the ICOAP patterns are equivalent for this particular association.

Taken together, our findings highlight the importance of the clinician’s understanding of the patient’s pain experience more broadly when considering symptomatic disease progression. As an initial step in this approach, clinicians can consider the factors we found to be significantly associated with the pain patterns and stages of disease. Identifying these factors in people with knee OA may in turn help clinicians apply pain management strategies accordingly and optimize their treatment.

This study has several limitations. It was a cross-sectional study, so we can report only on associations and not on causality. Our sample was relatively small, particularly the subsample of participants with constant pain, and one of convenience. We used the image from the Modified painDETECT Questionnaire to categorize the pain patterns; because the reliability and validity of this tool have yet to be evaluated, our findings may differ from those of studies that use the ICOAP patterns or other pattern definitions. In addition, we did not adjust for multiple comparisons. Future longitudinal studies with larger and more representative samples of participants with each pain pattern may help improve our understanding of these associations.

Conclusion

Ours is the first study to examine a wide range of pain-related factors and participant characteristics and thus adds to a more complex understanding of how personal, physical, psychological, pain, and nervous system factors relate to the three pain patterns in people with knee OA. This work has helped further characterize these pain patterns and can serve as the basis for generating hypotheses in future longitudinal studies seeking to optimize interventions to prevent or delay the transition from intermittent to constant or mixed pain.

Key Messages

What is already known about this topic

Knowledge is limited regarding the associations of pain-related factors and patient characteristics, particularly physical function, with intermittent and constant pain in people with knee OA. No study has examined factors associated with mixed pain.

What this study adds

Our cross-sectional analysis of people with knee OA found that sex, age, pain intensity, and self-reported function were significantly associated with the intermittent, constant, and mixed pain patterns. Knowledge of the relationships between these factors and the pain patterns can help clinicians target care and improve the management of patients’ pain.

References

  • 1.Vos T, Abajobir AA, Abate KH, et al. Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2017;390(10100):1211–59. 10.1016/S0140-6736(17)32154-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Bombardier C, Hawker G, Mosher D. The impact of arthritis in Canada: today and over the next 30 years. Toronto: Arthritis Alliance of Canada; 2016. [Google Scholar]
  • 3.Sharif B, Garner R, Hennessy D, et al. Productivity costs of work loss associated with osteoarthritis in Canada from 2010 to 2031. Osteoarthritis Cartilage. 2017;25(2):249–58. 10.1016/j.joca.2016.09.011. [DOI] [PubMed] [Google Scholar]
  • 4.Life with arthritis in Canada: a personal and public health challenge. Ottawa: Public Health Agency of Canada; 2010. [cited 5 Sep 2021]. Available from: https://www.phac-aspc.gc.ca/cd-mc/arthritis-arthrite/lwaic-vaaac-10/pdf/arthritis-2010-eng.pdf [Google Scholar]
  • 5.Pan F, Tian J, Aitken D, et al. Predictors of pain severity trajectory in older adults: a 10.7-year follow-up study. Osteoarthritis Cartilage. 2018;26(12):1619–26. 10.1016/j.joca.2018.08.002. [DOI] [PubMed] [Google Scholar]
  • 6.Carlesso LC, Hawker GA, Torner J, et al. Association of intermittent and constant knee pain patterns with knee pain severity and with radiographic knee osteoarthritis duration and severity. Arthritis Care Res (Hoboken). 2020; 73(6):788–93. 10.1002/acr.24194. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Hawker GA, Stewart L, French MR, et al. Understanding the pain experience in hip and knee osteoarthritis: an OARSI/OMERACT initiative. Osteoarthritis Cartilage. 2008;16(4):415–22. 10.1016/j.joca.2007.12.017. [DOI] [PubMed] [Google Scholar]
  • 8.Fingleton C, Smart K, Moloney N, et al. Pain sensitization in people with knee osteoarthritis: a systematic review and meta-analysis. Osteoarthritis Cartilage. 2015;23(7):1043–56. 10.1016/j.joca.2015.02.163. [DOI] [PubMed] [Google Scholar]
  • 9.French HP, Smart KM, Doyle F. Prevalence of neuropathic pain in knee or hip osteoarthritis: a systematic review and meta-analysis. Semin Arthritis Rheum. 2017;47(1):1–8. 10.1016/j.semarthrit.2017.02.008. [DOI] [PubMed] [Google Scholar]
  • 10.Carlesso LC, Segal NA, Curtis JR, et al. Knee pain and structural damage as risk factors for incident widespread pain: data from the Multicenter Osteoarthritis Study. Arthritis Care Res. 2017;69(6):826–32. 10.1002/acr.23086. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Altman R., Asch E., Bloch D., Bole G., Borenstein D., Brandt K., et al. Development of criteria for the classification and reporting of osteoarthritis. Classification of osteoarthritis of the knee. Diagnostic and Therapeutic Criteria Committee of the American Rheumatism Association. Arthritis Rheum. 1986;29(8):1039–49. [DOI] [PubMed] [Google Scholar]
  • 12.Daveluy C, Pica L, Audet N, et al. Enquête sociale et de santé 1998: cahier technique et méthodologique. Montréal: Institut de la statistique du Québec; 2001. [Google Scholar]
  • 13.Kellgren J, Lawrence J. Radiological assessment of osteo-arthrosis. Ann Rheum Dis. 1957;16(4):494. 10.1136/ard.16.4.494. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Katz JN, Chang LC, Sangha O, et al. Can comorbidity be measured by questionnaire rather than medical record review? Med Care. 1996;34(1):73–84. 10.1097/00005650-199601000-00006. [DOI] [PubMed] [Google Scholar]
  • 15.Blais F, Gendron L, Mimeault V, et al. Évaluation de l’insomnie: validation de trois questionnaires [Evaluation of insomnia: validation of three questionnaires]. L’Encéphale. 1997;23:447–53. [PubMed] [Google Scholar]
  • 16.Fillion L, Gélinas C, Simard S, et al. Validation evidence for the French Canadian adaptation of the Multidimensional Fatigue Inventory as a measure of cancer-related fatigue. Cancer Nurs. 2003;26(2):143–54. 10.1097/00002820-200304000-00008. [DOI] [PubMed] [Google Scholar]
  • 17.Collins N, Prinsen C, Christensen R, et al. Knee Injury and Osteoarthritis Outcome Score (KOOS): systematic review and meta-analysis of measurement properties. Osteoarthritis Cartilage. 2016;24(8):1317–29. 10.1016/j.joca.2016.03.010. [DOI] [PubMed] [Google Scholar]
  • 18.Roberge P, Doré I, Menear M, et al. A psychometric evaluation of the French Canadian version of the Hospital Anxiety and Depression Scale in a large primary care population. J Affect Disord. 2013;147(1–3):171–9. 10.1016/j.jad.2012.10.029. [DOI] [PubMed] [Google Scholar]
  • 19.Gierk B, Kohlmann S, Toussaint A, et al. Assessing somatic symptom burden: a psychometric comparison of the Patient Health Questionnaire–15 (PHQ–15) and the Somatic Symptom Scale–8 (SSS–8). J Psychosom Res. 2015;78(4):352–5. 10.1016/j.jpsychores.2014.11.006. [DOI] [PubMed] [Google Scholar]
  • 20.Sullivan MJ. The Pain Catastrophizing Scale: user manual. Montreal: McGill University; 2009. [Google Scholar]
  • 21.Scheier MF, Carver CS, Bridges MW. Distinguishing optimism from neuroticism (and trait anxiety, self-mastery, and self-esteem): a reevaluation of the Life Orientation Test. J Pers Soc Psychol. 1994;67(6):1063. 10.1037/0022-3514.67.6.1063. [DOI] [PubMed] [Google Scholar]
  • 22.Lacasse A, Bourgault P, Tousignant-Laflamme Y, et al. Development and validation of the French-Canadian Chronic Pain Self-Efficacy Scale. Pain Res Manag. 2015;20(2):75–83. 10.1155/2015/832875. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Kachooei AR, Ebrahimzadeh MH, Erfani-Sayyar R, et al. Short Form–McGill Pain Questionnaire–2 (SF-MPQ-2): a cross-cultural adaptation and validation study of the Persian version in patients with knee osteoarthritis. Arch Bone Jt Surg. 2015;3(1):45. [PMC free article] [PubMed] [Google Scholar]
  • 24.Hochman J, Gagliese L, Davis A, et al. Neuropathic pain symptoms in a community knee OA cohort. Osteoarthritis Cartilage. 2011;19(6):647–54. 10.1016/j.joca.2011.03.007. [DOI] [PubMed] [Google Scholar]
  • 25.Leveille SG, Ling S, Hochberg MC, et al. Widespread musculoskeletal pain and the progression of disability in older disabled women. Ann Intern Med. 2001;135(12):1038–46. 10.7326/0003-4819-135-12-200112180-00007. [DOI] [PubMed] [Google Scholar]
  • 26.Edwards RR, Dworkin RH, Turk DC, et al. Patient phenotyping in clinical trials of chronic pain treatments: IMMPACT recommendations. Pain. 2016;157(9):1851–71. 10.1097/j.pain.0000000000000602. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Rodriguez CS. Pain measurement in the elderly: a review. Pain Manag Nurs. 2001;2(2):38–46. 10.1053/jpmn.2001.23746. [DOI] [PubMed] [Google Scholar]
  • 28.Dobson F, Bennell KL, Hinman RS, et al. Recommended performance-based tests to assess physical function in people diagnosed with hip or knee osteoarthritis. Mount Laurel, NJ: Osteoarthritis Research Society International; 2013. [cited 5 Sep 2021]. Available from: https://www.oarsi.org/sites/default/files/docs/2013/manual.pdf. [DOI] [PubMed] [Google Scholar]
  • 29.Neogi T, Frey-Law L, Scholz J, et al. Sensitivity and sensitisation in relation to pain severity in knee osteoarthritis: trait or state? Ann Rheum Dis. 2015;74(4):682–8. 10.1136/annrheumdis-2013-204191. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Rabey M, Smith A, Beales D, et al. Differing psychologically derived clusters in people with chronic low back pain are associated with different multidimensional profiles. Clin J Pain. 2016;32(12):1015–27. 10.1097/ajp.0000000000000363. [DOI] [PubMed] [Google Scholar]
  • 31.Gervais-Hupé J, Pollice J, Sadi J, et al. Validity of the Central Sensitization Inventory with measures of sensitization in people with knee osteoarthritis. Clin Rheumatol. 2018;37(11):3125–32. 10.1007/s10067-018-4279-8. [DOI] [PubMed] [Google Scholar]
  • 32.Cathcart S, Winefield AH, Rolan P, et al. Reliability of temporal summation and diffuse noxious inhibitory control. Pain Res Manag. 2009;14(6):433–8. 10.1155/2009/523098. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Mutlu EK, Ozdincler AR. Reliability and responsiveness of algometry for measuring pressure pain threshold in patients with knee osteoarthritis. J Phys Ther Sci. 2015;27(6):1961–5. 10.1589/jpts.27.1961. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Wylde V, Palmer S, Learmonth I, et al. Test–retest reliability of quantitative sensory testing in knee osteoarthritis and healthy participants. Osteoarthritis Cartilage. 2011;19(6):655–8. 10.1016/j.joca.2011.02.009. [DOI] [PubMed] [Google Scholar]
  • 35.Yarnitsky D, Bouhassira D, Drewes A, et al. Recommendations on practice of conditioned pain modulation (CPM) testing. Eur J Pain. 2015;19(6):805–6. 10.1002/ejp.605. [DOI] [PubMed] [Google Scholar]
  • 36.Lewis GN, Luke H, Rice DA, et al. Reliability of the conditioned pain modulation paradigm to assess endogenous inhibitory pain pathways. Pain Res Manag. 2012;17(2):98–102. 10.1155/2012/610561. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Heinze G, Wallisch C, Dunkler D. Variable selection: a review and recommendations for the practicing statistician. Biom J. 2018;60(3):431–49. 10.1002/bimj.201700067. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Hoteit F, Feldman D, Pollice J, et al. A scoping review of pain and patient characteristics and function associated with intermittent and constant pain in people with knee OA. Physiother Can. 2020;73(2):118–28. 10.3138/ptc-2019-0049. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Arnstein P, Caudill M, Mandle CL, et al. Self efficacy as a mediator of the relationship between pain intensity, disability and depression in chronic pain patients. Pain. 1999;80(3):483–91. 10.1016/s0304-3959(98)00220-6. [DOI] [PubMed] [Google Scholar]
  • 40.Schneider S, Junghaenel DU, Keefe FJ, et al. Individual differences in the day-to-day variability of pain, fatigue, and well-being in patients with rheumatic disease: associations with psychological variables. Pain. 2012;153(4):813–22. 10.1016/j.pain.2012.01.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Zakoscielna KM, Parmelee PA. Pain variability and its predictors in older adults: depression, cognition, functional status, health, and pain. J Aging Health. 2013;25(8):1329–39. 10.1177/0898264313504457. [DOI] [PubMed] [Google Scholar]
  • 42.Birtwhistle R, Morkem R, Peat G, et al. Prevalence and management of osteoarthritis in primary care: an epidemiologic cohort study from the Canadian Primary Care Sentinel Surveillance Network. CMAJ Open. 2015;3(3):E270. 10.9778/cmajo.20150018. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Dahlhamer J, Lucas J, Zelaya C, et al. Prevalence of chronic pain and high-impact chronic pain among adults: United States, 2016. Morb Mortal Wkly Rep. 2018;67(36):1001. 10.15585/mmwr.mm6736a2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Song J, Chang AH, Chang RW, et al. Relationship of knee pain to time in moderate and light physical activities: data from Osteoarthritis Initiative. Semin Arthritis Rheum. 2018;47(5):683–8. 10.1016/j.semarthrit.2017.10.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Soni A, Kiran A, Hart DJ, et al. Prevalence of reported knee pain over twelve years in a community-based cohort. Arthritis Rheum. 2012;64(4):1145–52. 10.1002/art.33434. [DOI] [PubMed] [Google Scholar]
  • 46.Loeser RF. Aging and osteoarthritis. Curr Opin Rheumatol. 2011;23(5):492. 10.1097/bor.0b013e3283494005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Davison MJ, Ioannidis G, Maly MR, et al. Intermittent and constant pain and physical function or performance in men and women with knee osteoarthritis: data from the osteoarthritis initiative. Clin Rheumatol. 2016;35(2):371–9. 10.1007/s10067-014-2810-0. [DOI] [PMC free article] [PubMed] [Google Scholar]

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