Comparative Analysis of Health Domains for Neuropathic Pain Patients

Abstract

Active duty military members have significant service-related risks for developing pain from injury. Although estimates for neuropathic pain (NP) are available for civilian populations, the incidence and prevalence for NP in military members is less clear. Understanding correlates of pain in military members is vital to improving their physical, mental, and social health. Using a comparative design, a secondary analysis was conducted on longitudinal PASTOR data from 190 pain management center patients. The objectives were to compare trends in patient-reported outcomes over time between those screening positive and negative for NP (NP+, NP−, respectively) based on PROMIS Neuropathic Pain Scale T-scores. Findings showed improvements in fatigue, sleep-related impairment, and anger over time. There was a difference between those screening NP+ and NP− for sleep-related impairment, and the cross-level interaction effect showed sleep-related impairment worsening over time. These results emphasize the need to identify NP and implement and evaluate targeted therapies.

Keywords

specialty clinic health care settings clinical research areas innovations in clinical practice nursing actions nursing interventions neuropathy syndromes quality of life clinical research

Background and Significance

The International Association for the Study of Pain defines neuropathic pain (NP) as: “pain caused by a lesion or disease of the somatosensory system” (International Association for the Study of Pain, n.d.). Although NP is considered a chronic or persistent condition (pain lasting >3 months), acute NP precedes the progression to chronic NP (Gray, 2008), and evokes a cascade of physiological (peripheral and central sensitization) and neuropsychological (aversion and avoidance) events leading to persistent pain (Carr & Goudas, 1999). It is estimated that 6% to 8% of the general population with acute NP pain will develop persistent chronic NP (Freynhagen & Bennett, 2009) with the overall prevalence of chronic NP in the general population ranging from about 7% to 10% (van Hecke et al., 2014). Neuropathic pain is associated with multiple chronic conditions as well as trauma and surgical interventions (Clark et al., 2009; Kehlet et al., 2006). Regardless of type of NP, there is agreement that managing it is both complex and challenging (Cruccu & Truini, 2017).

Although estimates of NP are available for civilian populations, the incidence and prevalence of NP in active duty military members is less clear. Active duty military members have significant service-related risks for developing pain from injury associated with routine training and job performance and combat-related trauma (Hauret et al., 2010; Knox et al., 2011; Roy & Lopez, 2013).

Moreover, injuries resulting from blast, burns, or blunt trauma can result in the activation of multiple pain pathways such as NP (Clark et al., 2007), and amputation from major combat-related limb trauma may result in challenging NP conditions. Notwithstanding the advancements in military pain care, there is a paucity of literature addressing NP in the military population.

The importance of identifying correlates of pain in military members is vital to understanding and improving their physical, mental, and social health. Studies show that military members in pain have compromised physical functioning (Young-McCaughan et al., 2017) and may struggle with depression (Lippa et al., 2015; Young-McCaughan et al., 2017), sleep-related impairment (Brown et al., 2013; Lippa et al., 2015; Young-McCaughan et al., 2017), generalized anxiety (Higgins et al., 2014; Young-McCaughan et al., 2017), and anger (Lombardo et al., 2005). Systematic and comprehensive point of care collection of biopsychosocial patient-reported outcomes associated with pain can be used to guide therapeutic pain interventions and evaluate patient responses (Vallerand et al., 2015). The Pain Assessment Screening Tool and Outcomes Registry (PASTOR), used in selected military care settings since 2014 and now the standard assessment tool for use in military pain specialty clinics, accomplishes this goal. PASTOR incorporates the National Institutes of Health PROMIS^® (Patient-Reported Outcomes Measurement Information System) measures into an automated data collection system to capture pain and pain-related outcomes (Cook et al., 2017; Flynn et al., 2017).

This study used a pain management center PASTOR database to examine physical and mental health domains in longitudinal data of active duty military service members seeking care at a military interdisciplinary pain management center. The analysis compared trends in patient-reported outcomes over time between those screening positive and negative for NP (NP+, NP−, respectively) based on PROMIS Neuropathic Pain Scale T-scores. Two previous studies using this PASTOR database produced preliminary data for comparative effectiveness of pain therapies (Flynn et al., 2017), and validated PROMIS measures in a military population (Cook et al., 2017). As the first investigation to explore the association of NP with the physical and mental health domains in PASTOR with active duty military members, this research helps elucidate the correlates of NP and generates military population estimates for these PASTOR domains. Nurses are in a unique position to assess subtle changes in a patient’s physical and mental status that may be due to the effects of neuropathic pain.

Methods

Design: A longitudinal, descriptive comparative analysis of an existing PASTOR dataset.

Sample and Data Collection

Data included in this secondary analysis were obtained from the Madigan Army Medical Center (MAMC) in Tacoma, WA research protocol titled, “Retrospective Evaluation of Relationships among Pain Correlates and Psychometric Evaluation of the Measures that Estimate Them (Research Protocol #215049).” This parent study was a retrospective analysis of deidentified longitudinal PASTOR data collected from active duty military patients receiving routine pain care at the Madigan Interdisciplinary Pain Management Center (IPMC). The parent study protocol was determined to be exempt by the Madigan Institutional Review Board and informed consent was not required. The MAMC study included sociodemographic data of 640 patients seen in the Madigan IMPC as part of standard clinical care for pain-related conditions who completed at least one PASTOR assessment within the period between May 27, 2014 and March 31, 2015. Participants were ages ≥18 years, able to read and write English, and had a referral to the Madigan IMPC with a complaint of pain. Excluded from the parent study were patients who could not complete the computer-based survey due to cognitive impairment or physical limitations. All new patients to the IPMC for interdisciplinary care attended an orientation class where they were informed that PASTOR is an assessment tool that IPMC providers could use to develop treatment plans and monitor progress and response to therapies. Laptop computers with the PASTOR assessments were provided to patients at the end of their orientation class, and patients were instructed to complete PASTOR, but it was not a requirement for continued care. Patients were contacted prior to subsequent visits with a request to complete PASTOR. This could be accomplished prior to the appointment, on a personal device, or at a kiosk in the clinic. PASTOR data collected during the 10-month observation period was maintained in an electronic database and deidentified prior to transfer to researchers for analysis.

For the current study, data from patients with at least three PASTOR assessments (N = 190) were included. A minimum of three assessments were needed to show a potential nonlinear trend or pattern of change (Singer & Willet, 2003). The frequency of PASTOR assessments was contingent on prompts to patients by their pain medicine physicians coinciding with patient visits and/or the need to collect data to gauge the effectiveness of pain therapies. Assessment completion dates were evaluated to confirm that there were ≥14 days between each assessment, which was believed to be reasonable to allow time for changes in pain outcomes to be realized. For data collection points <14 days between assessments, these data points were eliminated, and the next assessment was included. Mean time between assessments one through five were 7.46, 7.33, 5.49, and 5.31 weeks.

Study Measures

PASTOR is a web-based survey tool of PROMIS measures developed for use by the Departments of Defense and Veterans Health Administration to assess and track biopsychosocial patient-reported outcomes for pain (Defense and Veterans Center for Integrative Pain Management, 2016). PASTOR employs computer adaptive testing (CAT), which tailors items to each individual by incorporating an algorithm using information derived from a previous item response to select the follow-on item (Cella et al., 2007; Flynn et al., 2017). PROMIS scores within PASTOR are standardized to the T-score metric, with a mean score of 50 and a standard deviation of 10, allowing for comparison of patients’ scores to a United States reference population (Cella et al., 2010).

The Defense and Veterans Pain Rating Scale (DVPRS) consists of a 0 to 10 numeric rating scale with word anchors, color coding, and facial representations of pain. Preliminary validation of the DVPRS and its enhancements of a numeric rating scale, was conducted with a convenience sample of 350 inpatient and outpatient AD or retired service members at the former Walter Reed Army Medical Center (Buckenmaier et al., 2013). The original DVPRS was later revised and further validated to incorporate a new set of facial depictions of pain (Polomano et al., 2016). Nassif et al. (2015) conducted a study of more than 200 VHA outpatients and found evidence for concurrent validity of the revised DVPRS. The adoption of the DVPRS is expected to facilitate the utilization of consistent metrics for defining pain levels as well as improve clinical encounters across transitions in care (Buckenmaier et al., 2013).

For this secondary analysis of 190 patients, PASTOR patient-reported data elements included the DVPRS pain intensity scale for average pain ratings and four supplemental questions, and PROMIS measures for physical function, fatigue, sleep-related impairment, depression, anxiety, and anger. Average pain intensity with the DVPRS was recalled over the past 7 days. The four DVPRS supplemental questions ask patients to rate (scale 0–10) how their pain impacts their activity, sleep, mood, and stress. Each PROMIS measure required a response to a minimum of four items to compute a T-score for the respective categories. All items in each category, except physical function, request pain-related information experienced over the past 7 days. Physical function emphasizes current capabilities and the item stems begin with phrases such as “Are you able to. . . .”

The PROMIS Neuropathic Pain Quality Scale (PROMIS PQ-Neuro, or PROMIS Neuropathic Pain Scale in PASTOR), consists of five items about pain in the past 7 days. Items capture the sensory component of NP (i.e., pins and needles, tingly, stinging, electrical, and numb) with responses scaled from 1 (not at all) to 5 (very much) (Askew, Cook, Keefe, et al., 2016). Based on T-score calculations from the PROMIS PQ-Neuro Scale, two cutoff points, ≥50 and ≥57, were used in this analysis to determine presence of NP+ (Askew, Cook, Keefe, et al., 2016). This screen is used to identify probable neuropathic pain if exceeding the cutoffs. These cut-off points were chosen based on prior research conducted by Askew et al. which established a T-score cutoff of ≥50 as having sensitivity of 0.77 and specificity of 0.70, and a T-score cutoff of ≥57 yielding sensitivity and specificity of 0.42 and 0.90, respectively (Askew, Cook, Keefe, et al., 2016). The two cut-offs have different sensitivity and specificity, thus allowing the investigators to assess which cut-offs are empirically associated with study outcomes. The Cronbach’s alpha in this sample was α = .749 for the five-item PROMIS Neuropathic Pain Scale in PASTOR.

Several studies support the validity and reliability of PROMIS measures in diverse samples (Askew, Cook, Revicki, et al., 2016; Cella et al., 2016; Cook et al., 2016; Hahn et al., 2016; Schalet et al., 2016). Cook et al. (2017) confirmed strong psychometric properties for PROMIS patient-reported measures in ongoing routine clinical care for a military population. To assess the sensitivity of the PROMIS Neuropathic Pain Scale in PASTOR of quantifying NP, provider diagnosis of NP for the 190 patients in this study was obtained through medical record abstraction and verified against PROMIS Neuropathic Pain Scale in PASTOR.

Statistical Analysis

Data analyses were performed using IBM SPSS Statistical Software version 24.0 (Armonk, New York). Power analysis was performed using a multilevel model approach (MLM). We estimated approximately 200 participants would be required to achieve a desired power of 80% given alpha equals .05 and a standardized effect size of 0.40 (moderate). Descriptive statistics on sociodemographic and military variables were conducted for the original sample (N = 640) and for the study cohort of 190 patients who completed at least three PASTOR assessments. Additional information from PASTOR was obtained for the study cohort on relationship of injury to deployment, and impact of pain on the ability to perform work. To assess if groups with complete and incomplete assessments were different, a comparison of the 450 patients who did not complete at least three PASTOR assessments and the 190 who completed at least three assessments was conducted using ANOVA and Chi-squared tests. A p-value <.05 was considered significant for all analyses in this investigation. DVPRS average pain intensity was compared between those cutoff T-scores of ≥50 and ≥57 using Mann Whitney U tests.

MLMs were employed for each outcome variable, testing a sequence of two models: (1) growth models and (2) cross-level interaction models. Growth models were used to examine outcomes over time and included fixed and random effects. Time was the time-varying predictor, which is a fixed effect, and the random coefficient (i.e., variance component) of interest were the intercepts unique to each individual. This model provided information on changes in the outcome variable over time (Singer & Willet, 2003). To further expand the growth model, separate cross-level interaction models were constructed using both the ≥50 and ≥57 T-scores at baseline as NP+ to analyze whether changes in patient-reported outcomes were simultaneously dependent on time and NP (Aguinis et al., 2013; Singer & Willet, 2003). To optimize specificity (i.e., to maximize the likelihood of eliminating patients NP− [Askew, Cook, Keefe, et al., 2016]) models were re-run with a T-score ≥57. The predictors and fixed effects for the cross-level interaction models were NP and time, the random effects were the intercepts, and the random errors were the residuals (i.e., intra-individual variability) unique to each individual for the outcome variable of interest. The regression coefficients and the variance components are reported for each model as well as Akaike’s Information Criterion (AIC) and Schwartz’s Bayesian Criterion (BIC). AIC and BIC were used to compare the sequence of models—the lower the number the better the model fit (Brauer & Curtin, 2018). Three respondents were not included in the cross-level interaction analysis due to missing or incomplete data in the PROMIS Neuropathic Pain Scale.

Results

Sample Characteristics

The 190 service members had a mean age of 35.06 years (SD = 8.62; median 34; range 20–59) and were predominately male (84%). Table 1 reports all sociodemographic data on eligible participants (N = 190) and those excluded (N=450). There were no statistical differences on socio-demographics variables with the exception of military status and branch of service.

Table 1.

Sample Descriptive Statistics.

Variable	Categories	n Eligible (%)*
Gender	Female	31 (16)
	Male	159 (84)
	Total	190 (100)
Education	Less than high school	0 (0)
	Advanced degree (MA, PhD, MD)	16 (9)
	College degree (BA, BS)	29 (15)
	High school grad or GED	41 (22)
	Some college or technical degree	102 (54)
	Total	188 (100)
Marital status	Not married	46 (25)
	Married	141 (75)
	Total	187 (100)
Military status	Active duty	178 (96)
	Guard/reserve/military retired/civilian	8 (4)
	Total	186 (100)
Rank	Enlisted	157 (86)
	Officer	20 (11)
	Warrant officer	6 (3)
	Total	183 (100)
Branch	Air force	10 (5.5)
	Army	170 (93)
	Navy	2 (1)
	Coast guard/marines/federal service	1 (0.5)
	Total	183 (100)
Limit hours per week	No	81 (43)
	Yes	108 (57)
	Total	189 (100)
When injury occurred	During deployment	69 (37)
	Not deployment related	82 (44)
	Post-deployment	14 (8)
	Pre-deployment	21 (11)
	Total	186 (100)

Valid percentage represented based on the number of respondents.

Pain Severity and NP Diagnosis

The mean DVPRS average pain intensity for NP+ and NP− using the PROMIS Neuropathic Pain Scale cutoffs of 50 and 57 by the first five assessment time points was calculated. The mean DVPRS average pain intensity for the entire sample at the first assessment was 5.80 (SD = 1.43), indicating moderate pain severity. There were no significant differences in average pain ratings by assessments between patients NP+ or NP− at the T-score ≥50. However, significantly higher mean average pain ratings were observed for patients with NP+ using the T-score ≥57 at assessment points two, three, and five (p = .009, .010, and .038, respectively). Details at each time point are reported in the Supplemental Appendix.

A provider diagnosis of NP was documented in the medical record for 27% of the 190 patients. By the two T-score cutoffs for the PROMIS Neuropathic Pain Scale in PASTOR, 75% (n = 142) of patients NP+ at ≥50, and 36% (n = 68) NP+ at ≥57. A larger percentage of patients had evidence of probable NP using findings from PASTOR data compared to providers’ diagnoses appearing in patients’ health records. Cohen’s kappa (κ) statistics were calcuated for percent agreement in classification of NP between the provider and PASTOR NP T-scores cutoffs of ≥50 and ≥57 yielding extremely poor agreements of κ = 0.005 and κ = 0.109. The most common pain syndromes associated with NP were lumbar radiculopathy, and cervical radiculopathy.

Multilevel Modeling

Separate MLMs were tested for each of the six PROMIS measure outcome variables: physical function, fatigue, sleep-related impairment, depression, anxiety, and anger. A detailed description of each PROMIS measure and descriptive statistics for T-scores for all PASTOR measures appear in Table 2 for PROMIS Neuropathic Pain Scale screen at T-score ≥50 and Table 3 for T-score ≥57.

Table 2.

Descriptive Data for PASTOR Measures by Assessment for PROMIS Neuropathic Pain Scale T-Score for NP > 50.*

PASTOR PROMIS measures	Assessment 1		Assessment 2		Assessment 3		Assessment 4		Assessment 5
PASTOR PROMIS measures	n, mean (SD)	CI (T-score range)	n, mean (SD)	CI (T-score range)	n, mean (SD)	CI (T-score range)	n, mean (SD)	CI (T-score range)	n, mean (SD)	CI (T-score range)
Physical function
Non-NP	45, 40.75 (4.98)	39.25–42.25 (32.21–50.11)	42, 40.54 (5.19)	38.92–42.15 (28.58–53.11)	41, 41.23 (6.48)	39.18–43.28 (29.58–67.74)	22, 41.10 (7.65)	37.71–44.49 (29.58–65.58)	7, 41.16 (10.32)	31.62–50.70 (23.47–50.97)
NP	142, 39.64 (6.05)	38.64–40.65 (24.67–61.04)	129, 39.56 (5.50)	38.60–40.52 (24.67–61.04)	133, 39.56 (6.11)	38.51–40.61 (20.03–62.90)	75, 39.25 (5.54)	37.98–40.53 (26.84–51.28)	38, 40.54 (7.31)	38.14–42.94 (27.23–61.26)
Fatigue
Non-NP	45, 57.29 (8.51)	54.73–59.85 (41.16–73.94)	42, 57.45 (7.94)	54.98–59.93 (42.49–76.03)	41, 58.74 (8.79)	55.97–61.52 (29.11–73.94)	22, 58.27 (10.16)	53.77–62.78 (29.11–73.94)	7, 50.66 (11.00)	40.49–60.83 (29.11–64.25)
NP	142, 58.79 (9.46)	57.22–60.36 (34.29–79.51)	129, 58.91 (8.67)	57.40–60.42 (29.11–79.51)	133, 57.83 (9.10)	56.27–59.39 (29.11–79.51)	75, 58.24 (9.22)	56.12–60.36 (34.29–76.03)	38, 56.94 (10.90)	53.35–60.52 (29.11–74.31)
Sleep-related impairment
Non-NP	45, 59.23 (8.89)	56.56–61.90 (41.66–77.08)	42, 60.19 (8.97)	57.39–62.98 (38.75–77.08)	41, 58.87 (9.09)	56.00–61.74 (30.30–77.08)	22, 58.90 (10.76)	54.13–63.67 (37.42–79.61)	7, 53.58 (11.07)	43.34–63.82 (34.45–68.62)
NP	142, 60.70 (8.11)	59.36–62.05 (30.30–77.08)	129, 60.69 (8.49)	59.21–62.16 (35.72–79.61)	133, 60.05 (9.04)	58.50–61.61 (30.30–79.61)	75, 59.48 (10.47)	57.07–61.89 (30.30–79.61)	38, 58.11 (10.44)	54.68–61.54 (34.45–77.08)
Depression
Non-NP	45, 50.79, (8.25)	48.31–53.27 (35.88–75.76)	42, 51.00 (10.00)	47.88–54.11 (35.88–78.05)	41, 52.36 (9.11)	49.49–55.24 (35.88–75.24)	22, 53.47 (9.90)	49.08–57.86 (35.88–78.05)	7, 52.86 (11.57)	42.16–63.56 (35.88–69.45)
NP	142, 51.70 (9.97)	50.05–53.35 (35.88–76.48)	127, 52.09 (10.05)	50.33–53.85 (35.88–78.05)	132, 52.05 (10.46)	50.25–53.85 (35.88–80.69)	74, 52.13 (9.39)	49.95–54.30 (35.88–73.10)	38, 51.30 (10.60)	47.81–54.78 (35.88–68.97)
Anxiety
Non-NP	45, 55.12 (8.31)	52.62–57.62(35.37–73.44)	42, 54.27 (10.16)	51.11–57.44 (35.37–76.19)	41, 54.17 (10.07)	50.99–57.35 (35.37–75.76)	22, 55.11 (10.85)	50.30–59.92 (35.37–72.01)	7, 56.86 (10.17)	47.45–66.27 (41.34–73.44)
NP	142, 56.44 (9.39)	54.88–58.00 (35.37–76.19)	127, 56.64 (10.14)	54.86–58.42 (35.37–76.24)	132, 55.70 (10.38)	53.91–57.48 (35.37–84.30)	73, 56.76 (9.45)	54.56–58.97 (35.37–75.26)	38, 54.19 (11.26)	50.49–57.89 (35.37–82.32)
Anger
Non-NP	45, 55.53 (10.83)	52.28–58.79 (30.97–81.22)	42, 54.80 (10.74)	51.46–58.15 (30.97–71.58)	41, 54.70 (11.37)	51.11–58.29 (30.97–73.79)	22, 54.73 (11.96)	49.43–60.04 (30.97–76.97)	7, 53.84 (13.37)	41.48–66.21 (30.97–73.04)
NP	142, 55.53 (10.86)	53.72–57.33 (30.97–81.96)	127, 55.55 (10.76)	53.67–57.44 (30.97–79.95)	132, 54.45 (11.22)	52.51–56.38 (30.97–81.96)	73, 54.89 (11.50)	52.21–57.57 (30.97–81.96)	38, 51.50 (13.28)	47.13–55.86 (30.97–78.20)

Note. Non-NP = screen negative for neuropathic pain; NP = screen positive for neuropathic pain; SD = standard deviation; CI = confidence interval with lower and upper limits.

Three respondents did not have a T-score for neuropathic pain due to missing or incomplete data; Descriptive data not displayed for assessments 6 through 8 due to small sample sizes (n ≤ 15).

Physical health	Physical function is multidimensional and measured by a person’s ability to perform tasks ranging from low-level activities of daily living to high-level physical function such as endurance and strength activities.
	Fatigue is defined as an inability to perform basic tasks due to “an overwhelming and sustained sense of exhaustion” that interferes with one’s work and interaction in family and social situations.
	Sleep-related impairment is focused on functional deficiencies associated with sleep problems or decreased alertness, and the patient’s perception of alertness, sleepiness, and tiredness.
Mental health	Depression focuses on negative deficits such as “negative mood (e.g., sadness, guilt), decreased positive affect (e.g., loss of interest), information processing deficits (e.g., problems in decision-making), negative views of the self (e.g., self-criticism, worthlessness), and negative social cognition (e.g., loneliness, interpersonal alienation).”
	Anxiety is measured through a patient’s report of “fear (e.g., fearfulness, feelings of panic), anxious misery (e.g., worry, dread), hyperarousal (e.g., tension, nervousness, restlessness), and somatic symptoms related to arousal (e.g., cardiovascular symptoms, dizziness).”
	Anger focuses on “angry mood (e.g., irritability, reactivity), negative social cognition (e.g., interpersonal sensitivity, envy, vengefulness), verbal aggression, and efforts necessary to control angry mood.”

Source. Cella et al. (2010).

Table 3.

Descriptive Data for PASTOR Measures by Assessment for PROMIS Neuropathic Pain Scale T-Score for NP > 57.*

PASTOR PROMIS measures	Assessment 1		Assessment 2		Assessment 3		Assessment 4		Assessment 5
PASTOR PROMIS measures	n, mean (SD)	95% CI (T-score range)	n, mean (SD)	95% CI (T-score range)	n, mean (SD)	95% CI (T-score range)	n, mean (SD)	95% CI (T-score range)	n, mean (SD)	95% CI (T-score range)
Physical function
Non-NP	119, 40.50 (5.90)	39.43–41.57 (24.82–61.04)	107, 40.45 (5.47)	39.40–41.50 (28.58–61.04)	111, 40.25 (6.70)	38.99–41.51 (20.03–67.74)	64, 40.30 (5.98)	38.81–41.79 (29.58–65.58)	29, 41.76 (7.24)	39.00–44.51 (23.47–53.11)
NP	68, 38.87 (5.57)	37.52–40.22 (24.67–52.75)	64, 38.71 (5.22)	37.40–40.01 (24.67–51.28)	63, 39.43 (5.29)	38.10–40.77 (29.58–55.83)	33, 38.45 (6.19)	36.26–40.65 (26.84–51.28)	16, 38.61 (8.35)	34.16–43.06 (27.23–61.26)
Fatigue
Non-NP	119, 57.78 (9.27)	56.10–59.47 (34.29–76.03)	107, 57.65 (8.20)	56.08–59.22 (42.49–79.51)	111, 57.71 (9.27)	55.97–59.46 (29.11–79.51)	64, 57.92 (9.57)	55.53–60.31 (29.11–73.94)	29, 53.98 (10.90)	49.83–58.13 (29.11–74.31)
NP	68, 59.55 (9.16)	57.33–61.77 (34.29–79.51)	64, 60.06 (8.83)	57.86–62.27 (29.11–79.51)	63, 58.64 (8.57)	56.48–60.79 (29.11–73.94)	33, 58.87 (9.13)	55.64–62.11 (39.05–76.03)	16, 59.54 (10.67)	53.86–65.23 (34.29–73.94)
Sleep-related impairment
Non-NP	119, 59.50 (8.22)	58.01–60.99 (38.75–77.08)	107, 59.31 (8.55)	57.67–60.95 (35.72–79.61)	111, 59.13 (9.39)	57.36–60.90 (30.30–79.61)	64, 58.93 (10.33)	56.35–61.52 (30.30–79.61)	29, 53.41 (9.44)	49.82–57.01 (34.45–68.62)
NP	68, 61.83 (8.31)	59.82–63.85 (30.30–77.08)	64, 62.66 (8.29)	60.59–64.73 (36.37–79.61)	63, 60.92 (8.33)	58.82–63.01 (38.75–72.48)	33, 60.14 (10.89)	56.28–64.00 (36.37–79.61)	16, 64.63 (8.54)	60.08–69.18 (52.51–77.08)
Depression
Non-NP	119, 51.12 (9.27)	49.44–52.80 (35.88–76.48)	105, 51.19 (9.81)	49.29–53.09 (35.88–78.05)	111, 52.77 (9.77)	50.93–54.61 (35.88–76.88)	64, 51.93 (9.21)	49.63–54.23 (35.88–78.05)	29, 50.12 (10.62)	46.09–54.16 (35.88–69.45)
NP	68, 52.11 (10.11)	49.66–54.56 (35.88–74.36)	64, 52.84 (10.34)	50.26–55.43 (35.88–78.05)	62, 50.97 (10.73)	48.24–53.69 (35.88–80.69)	32, 53.44 (10.04)	49.82–57.06 (35.88–73.10)	16, 54.11 (10.51)	48.51–59.71 (35.88–67.54)
Anxiety
Non-NP	119, 55.34 (8.61)	53.77–56.90 (35.37–73.44)	105, 54.79 (9.87)	52.88–56.70 (35.37–76.19)	111, 55.16 (10.21)	53.24–57.08 (35.37–76.24)	63, 55.28 (9.38)	52.92–57.65 (35.37–72.01)	29, 53.32 (10.33)	49.39–57.25 (35.37–73.44)
NP	68, 57.50 (9.91)	55.10–59.90 (35.37–76.19)	64, 58.13 (10.39)	55.54–60.73 (35.37–76.24)	62, 55.65 (10.53)	52.98–58.33 (35.37–84.30)	32, 58.53 (10.26)	54.84–62.23 (35.37–75.26)	16, 56.92 (12.19)	50.43–63.42 (35.37–82.32)
Anger
Non-NP	119, 55.47 (10.16)	53.63–57.32 (30.97–81.96)	105, 54.74 (11.08)	52.59–56.88 (30.97–79.95)	111, 54.93 (11.15)	52.83–57.03 (30.97–81.49)	63, 54.43 (11.25)	51.60–57.26 (30.97–80.31)	29, 49.52 (13.08)	44.55–54.50 (30.97–78.20)
NP	68, 55.63 (11.97)	52.73–58.53 (30.97–80.51)	64, 56.41 (10.11)	53.88–58.93 (30.97–74.25)	62, 53.75 (11.39)	50.85–56.64 (30.97–81.96)	32, 55.69 (12.25)	51.27–60.10 (34.15–81.96)	16, 56.10 (12.64)	49.37–62.84 (37.06–77.51)

Note. Non-NP = screen negative for neuropathic pain; NP = screen positive for neuropathic pain; SD = standard deviation; CI = confidence interval with lower and upper limits.

Three respondents did not have a T-score for neuropathic pain due to missing or incomplete data; Descriptive data not displayed for assessments 6 through 8 due to small sample sizes (n ≤ 15).

Physical health	Physical function is multidimensional and measured by a person’s ability to perform tasks ranging from low-level activities of daily living to high-level physical function such as endurance and strength activities.
	Fatigue is defined as an inability to perform basic tasks due to “an overwhelming and sustained sense of exhaustion” that interferes with one’s work and interaction in family and social situations.
	Sleep-related impairment is focused on functional deficiencies associated with sleep problems or decreased alertness, and the patient’s perception of alertness, sleepiness, and tiredness.
Mental health	Depression focuses on negative deficits such as “negative mood (e.g., sadness, guilt), decreased positive affect (e.g., loss of interest), information processing deficits (e.g., problems in decision-making), negative views of the self (e.g., self-criticism, worthlessness), and negative social cognition (e.g., loneliness, interpersonal alienation).”
	Anxiety is measured through a patient’s report of “fear (e.g., fearfulness, feelings of panic), anxious misery (e.g., worry, dread), hyperarousal (e.g., tension, nervousness, restlessness), and somatic symptoms related to arousal (e.g., cardiovascular symptoms, dizziness).”
	Anger focuses on “angry mood (e.g., irritability, reactivity), negative social cognition (e.g., interpersonal sensitivity, envy, vengefulness), verbal aggression, and efforts necessary to control angry mood.”

Source. Cella et al. (2010).

The growth model analysis showed time was statistically significant for fatigue (B = −0.48, p = .003), sleep-related impairment (B = −0.55, p = .001), and anger (B = −0.57, p = .002). Time was not significant for physical function, depression, or anxiety. For a T-score ≥57, there was a significant difference between those with NP− and NP+ for sleep-related impairment (B = −2.98, p = .011). At NP ≥57, the cross-level interaction was significant for sleep-related impairment (B = −0.84, p = .020), suggesting an interaction effect between time and NP ≥57. Those NP+ had worsening sleep-related impairment over time, and those NP− had improvement in sleep-related impairment over time (See Figure 1). Patients pain states were not static. Some patients flipped between NP+ and NP− based on their PROMIS Neuropathic Pain Scale screen cutoff T-scores during their course of treatment, with an upper limit of 15.8% of patients that flipped at any one assessment.

Discussion

A primary outcome of this study is the importance of measuring multivariable patient-reported biopsychosocial pain outcomes in a military population. Given that NP is associated with a decreased quality of life (O’Connor, 2009), physical, emotional and social functioning impairment, and sleep interference (Jensen et al., 2007), tracking comprehensive patient data is essential to gauge responses to treatment. Unlike acute pain without a neuropathic component, which usually occurs in response to a noxious stimuli and is short-lived, NP is typically chronic and leads to maladaptive changes in the peripheral and central nervous system often requiring mechanism-specific targeted therapies (Woolf, 2004). Additionally, sensory symptoms from NP such as burning, stabbing, and shock-like pain can be more difficult to manage than pain sensations without a neuropathic origin (Jensen et al., 2001). Studies report that most patients with NP do not often achieve pain relief even with aggressive treatment (Finnerup et al., 2010), and therapies that are effective for pain without a neuropathic origin may not be effective for NP (Smith, 2012). Drug therapy, including certain antidepressants and anticonvulsants, as well as non-pharmacological treatments such as exercise, acupuncture, and behavioral therapy, may provide some relief of neuropathic pain (Belgrade, 1999; Freynhagen & Bennett, 2009; Qaseem et al., 2017). Specifically at the IPMC, patients may be offered any one or more of the following approaches: education on effective self-management approaches; medications; interventional procedures; and interdisciplinary programs comprised of behavioral therapies, functional restoration approaches, and/or complementary and integrative health therapies.

The results of this analysis demonstrate overall improvements across time for a population of active duty military personnel reporting pain-related outcomes for fatigue, sleep-related impairment, and anger. This is a noteworthy observation as fatigue and sleep-related impairment are considered risk factors in the military environment, and are attributed to performance error, poor work performance, and potentially increased military accident rates (Bray et al., 2010; Caldwell & Caldwell, 2005). Problems with pain, sleep, and fatigue have been previously documented in 1,522 post-deployment infantry soldiers, as symptoms most commonly identified from the Patient Health Questionnaire (Toblin et al., 2012). Moreover, recognizing that patients in the IPMC were receiving care to manage pain, it is not surprising to find a decrease in anger over time. This is consistent with a study of veterans where pain intensity was positively associated with maladaptive anger management (Lombardo et al., 2005). Anger is harmful to the physical, psychological, and social well-being of persons with pain, and can negatively affect interpersonal relationships (Fernandez & Turk, 1995). It can also impede communication and progression in therapy, whereas decreased anger may facilitate a positive patient-provider interaction and increased compliance (Fernandez & Turk, 1995), potentially leading to improvements in other outcomes.

Our observed patterns for pain-related outcomes over time contribute to understanding the use of PASTOR data in specialty pain care programs. The lack of statistically significant improvements in several of the PASTOR measures over time might be attributed to resilience of active duty military members with pain and service responsibilities requiring them to remain physically active (Carragee & Cohen, 2009). For example, anxiety and physical function did show a trend toward improvement over time. This trend aligns with studies addressing anxiety (Higgins et al., 2014) and physical function (Young-McCaughan et al., 2017) that stress the importance of identifying correlates of pain, and that changes in physical and mental outcomes do not occur in isolation (Dodd et al., 2001). In contrast, there was a worsening for depression measured over time. Utilizing a baseline and follow-up assessment from the larger original PASTOR dataset used in this study, Flynn et al. (2017) also found worse outcomes for depression, in addition to anxiety, and anger. The authors surmised that worsening of these PASTOR outcomes may be due to the lack of perceived progress despite aggressive pain therapies and military members working hard to get better (Flynn et al., 2017). In contrast, our study noted a trend toward improvements in anxiety and anger, which was possibly due to our subset of patients having at least three assessments, thereby allowing more opportunity to capture perceived improvements. Finally, it may be necessary to isolate depression in future studies to determine predictors, such as other external factors, that might have contributed to the worsening of depression over time.

This study also found a significant cross-level interaction at the PASTOR Neuropathic Pain Scale T-score ≥57, reporting the two predictors, time and NP, interact for sleep-related impairment. The trajectories for sleep-related impairment were significantly different for NP+ and NP−. Participants NP+ (at ≥57 T-score) reported increasingly higher levels of sleep-related impairment than participants negative for NP. Studies have documented that NP increases in intensity throughout the day, peaking at night and impairing sleep (Belgrade, 1999; Mehta et al., 2016). Evidence suggests that sleep-related deficits in physical performance, cognition, alertness, and reasoning, all of which are critical to day-to-day operations of the military, can lead to negative consequences (Bray et al., 2010; Wesensten & Balkin, 2013). We did not observe statistically significant cross-level interactions for NP using the T-score ≥50. The NP cut-off score ≥50 has lower specificity compared to ≥57, thus less likely to correctly identify those who truly do not have the condition. For NP ≥57, the only significant interaction was for sleep-related impairment. If patients with chronic NP were studied over a longer time frame, it may have been possible to detect significant changes in the other variables. Lastly, we did not have sufficient sample size to divide the study population into respondents and non-respondents in order to determine if specific treatments offered in the IPMC were associated with likelihood of treatment response.

A patient may have flipped between neuropathic and non-neuropathic pain. This was not unexpected; NP conditions flare and abate over time, corresponding with the natural history of the underlying condition, psychosocial stressors, and response to treatment.

The PROMIS Neuropathic Pain Scale elicited the degree to which respondents experienced NP features in the past 7 days (1 [not at all] to 5 [very much]). While NP is largely stable overtime at a group level, individual variations are expected and may be significant over time (Giske et al., 2009), resulting from baseline pain, NP treatment, type and severity of other symptoms, and comorbidities. Also, more study participants reported NP symptoms NP+ cutoffs ≥50 and ≥57 than were diagnosed by providers. This demonstrates that the PASTOR NP screen may be more sensitive in quantifying the severity of NP symptoms compared to a provider diagnosis alone. Although the PROMIS Neuropathic Pain Scale is not intended as a diagnostic test, it should be used in conjunction with a thorough physical assessment to more comprehensively diagnose NP pain and to guide treatment plans (Askew, Cook, Keefe, et al., 2016).

The findings of this study have important implications for nursing interventions by supporting the need to assess and track pain-related biopsychosocial outcomes of NP. Specifically, nurses play a key role in recognizing the relationships of pain-related outcomes. Addressing sleep-related impairment may lead to improvement in other pain-related outcomes, and faster return to optimal function. Additionally, as champions of evidence-based care, nurses are vital to promoting the consistent use of standardized measures that can provide useful information to guide clinical care.

Limitations

The findings of this study should be interpreted in the context of the following limitations. The dataset included outcomes from military service members receiving care at one pain center, which may limit the generalizability to other pain care settings. A lack of significant findings in some PASTOR subscales could be attributed to the limited number of assessments per participant and a 10-month time frame, which did not allow for repeated PASTOR data points with a larger sample. The sample size decreased with each assessment and markedly after assessment four. Almost 90% of the study participants consisted of Army personnel, which may limit the generalizability of the findings to other military populations. Finally, we were not able to examine past and current pain and other health information not linked to PASTOR that might help identify predictors for poorer or better PASTOR outcomes.

Conclusion

The PASTOR measures provide useful outcomes to augment clinical diagnosis of pain and pain-related co-existing biopsychosocial problems, guide clinical care, and gauge responses to pain therapies. This study demonstrated that military service members treated in an interdisciplinary pain management center had trends for improvements in levels of fatigue, sleep-related impairment, and anger over time. These results emphasize the importance of addressing sleep-related impairment for patients with NP, which is vital to work performance and potentially beneficial to positively influencing other physical, mental, and social domains. With the incorporation of the PROMIS Neuropathic Pain Scale into PASTOR, there are further opportunities to diagnose NP-based patient-reported symptoms and T-score cutoffs, which is invaluable to identifying NP and implementing and evaluating targeted therapies for NP in military personnel. Lastly, as a result of this analysis suggesting that providers documented neuropathic pain much less than patients screened positive for it, a NP alert has been added a to the PASTOR report.

Supplemental Material

sj-docx-1-cnr-10.1177_10547738211030640 – Supplemental material for Comparative Analysis of Health Domains for Neuropathic Pain Patients

Supplemental material, sj-docx-1-cnr-10.1177_10547738211030640 for Comparative Analysis of Health Domains for Neuropathic Pain Patients by Christine Bader, Diane Flynn, Chester Buckenmaier, Catherine McDonald, Salimah Meghani, Christian Calilung and Rosemary Polomano in Clinical Nursing Research

Footnotes

Copyright Protection

Our team is comprised partly of employees of the US Government. This work was prepared as part of our official duties. Title 17 U.S.C. 105 provides that “Copyright protection under this title is not available for any work of the United States Government.” Title 17 U.S.C. 101 defines a U.S. Government work as a work prepared by a military service member or employee of the US Government as part of that person’s official duties.

Disclaimer

The views expressed in this manuscript are those of the authors and do not necessarily reflect the official policy of the Department of Defense or the United States Government.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by Robert Wood Johnson Future of Nursing Scholars program.

ORCID iDs

Christine Bader

Catherine McDonald

Rosemary Polomano

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Christine Bader, PhD, RN is an independent health consultant who previously served in senior health positions for the Veterans Affairs Administration and the Department of Defense. She earned her PhD at the University of Pennsylvania School of Nursing (Robert Wood Johnson Foundation Future of Nursing Scholar).

Diane Flynn, MD, Department of Rehabilitative Medicine, Madigan Army Medical Center, 9040 Jackson Avenue, Tacoma, WA 98431, USA.

Chester Buckenmaier MD, Director, Defense and Veterans Center for Integrative Pain Management, Professor of Anesthesiology, Department of Military and Emergency Medicine, Uniformed Services University.

Catherine McDonald, PhD, RN, FAAN, Associate Professor, University of Pennsylvania, School of Nursing, Perelman School of Medicine at the University of Pennsylvania, Center for Injury Research and Prevention, The Children’s Hospital of Philadelphia.

Salimah Meghani, PhD, MBE, RN, FAAN, Professor and Term Chair of Palliative Care, Department of Biobehavioral Health Sciences, Associate Director, NewCourtland Center for Transitions and Health, Senior Fellow, Leonard Davis Institute of Health Economics University of Pennsylvania.

Christian Calilung, MS, Project Coordinator, Defense and Veterans Center for Integrative Pain Management (DVCIPM), Henry M. Jackson Foundation for the Advancement of Military Medicine (HJF).

Rosemary Polomano, PhD, RN, FAAN, Associate Dean for Practice, Professor of Pain Practice, University of Pennsylvania, School of Nursing, Professor of Anesthesiology and Critical Care, Perelman School of Medicine, University of Pennsylvania.

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