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Article

Characteristics and Perioperative Risk Factors for Persistent Pain after Breast Cancer Surgery: A Prospective Cohort Study

by
Sachin Sahni
1,
Ronak Patel
1,
Li Wang
2,3,
Sarah Miles
4,
Elad Dana
5,6,7,* and
James S. Khan
1,5
1
Department of Anesthesia and Pain Medicine, University of Toronto, Toronto, ON M5G 1E2, Canada
2
Department of Anesthesia, McMaster University, Hamilton, ON L8S 4L8, Canada
3
Michael G. DeGroote Institute for Pain Research and Care, McMaster University, Hamilton, ON L8S 4L8, Canada
4
Department of Anesthesia and Pain Management, University Health Network, Toronto, ON M5G 2C4, Canada
5
Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada
6
Department of Anesthesia, Intensive Care and Pain Medicine, Meir Medical Center, Kfar Saba 4428164, Israel
7
Sackler School of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
*
Author to whom correspondence should be addressed.
Surgeries 2023, 4(3), 301-316; https://doi.org/10.3390/surgeries4030031
Submission received: 11 May 2023 / Revised: 9 June 2023 / Accepted: 19 June 2023 / Published: 22 June 2023
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Abstract

:
Objective: Persistent pain is a common complication after breast cancer surgery. We sought to determine the characteristics of persistent pain after breast cancer surgery and identify perioperative risk factors associated with its development. Methods: This prospective cohort study uses data from a prior randomized controlled trial of 100 patients undergoing breast cancer surgery. Patients were assessed on the presence and characteristics of pain at 3 months after surgery. Baseline and perioperative data were explored for potential associations with persistent pain in univariate and multivariate logistic regression models. Results: Fifty-three percent of patients reported persistent pain 3-months after surgery. Pain was primarily located in the axilla, chest, and shoulder, with the vast majority of patients with pain (96.2%) reporting a neuropathic pain feature. The mean intensity of pain was 2.5 (standard deviation [SD] 2.4, on a 0 to 10 pain scale) and persistent pain was associated with worse quality of life scores (p = 0.004) and increased use of analgesics (p = 0.015). Variables found to be associated with persistent pain in our univariable and multivariable-adjusted analyses were preoperative employment (OR 2.70, 95% CI 1.04–9.66, p = 0.042), acute postoperative pain during movement (OR 1.63, 95% CI 1.06–2.51, p = 0.027), and adjuvant chemotherapy (OR 3.30, 95% CI 1.19 to 9.15, p = 0.022). Conclusions: Persistent pain after breast cancer surgery is neuropathic and is associated with reduced quality of life and increased analgesic need. Future research should focus on perioperative interventions to reduce acute postoperative pain and consideration of modified adjuvant chemotherapy regimens to address modifiable risk factors and potentially reduce the incidence of persistent pain after breast cancer surgery.

1. Introduction

Breast cancer is one of the most diagnosed cancers in the world, and with improved survival and a high incidence rate, it is the most prevalent cancer among women in the USA with 2.6 million women reporting a history of the disease [1,2]. In 2018, there were nearly 2.1 million new breast cancer cases, accounting for more than 10% of all cancer diagnoses across both sexes [3]. Fortunately, with improvements in management, the 5-year breast cancer survival rate now approaches 90% [4]. Surgery is a critical component in breast cancer management and involves either a mastectomy (surgical removal of the entire breast) or a lumpectomy (removing only cancerous tissue and a rim of normal tissue). However, since patients with breast cancer are living longer, long-term complications of management and surgery are becoming increasingly apparent [5].
Persistent pain is a devastating yet common complication after breast cancer surgery. The International Association for the Study of Pain (IASP) defines persistent pain after surgery as pain localized to the surgical field or area, or innervation territory, that persists beyond the healing process (i.e., at least 3 months after surgery) [6]. A meta-analysis of 146 observational studies (137,675 patients) found that the median prevalence of any type of persistent pain after breast cancer surgery was 37% (IQR 22–48%) 3 to >120 months after surgery [7]. One reason for this high prevalence after breast cancer surgery is due to the rich neuronal innervation of the breast tissue and chest wall (Figure 1) [8]. Longitudinal data also suggest that this pain disorder is chronic and that over 50% of those diagnosed will continue to suffer from it 7–12 years after surgery [9]. The pain intensity experienced by those afflicted is not trivial and the median intensity of pain is estimated to be 3.9 cm (95% CI 3.6 to 4.2) on a 0 to 10 cm visual analog scale (VAS). Further, 20% of patients (95% CI 17–23%; 78 studies, 29,939 patients) suffer from moderate-to-severe pain [7].
Persistent pain also has negative consequences on patients’ sleep, function, social interactions, mood and psychological well-being, and quality of life [9,10,11,12,13,14]. Furthermore, economic analyses suggest that persistent pain after breast cancer surgery places an immense financial burden on the healthcare system, totaling about $1 billion USD annually to the US healthcare system alone [15].
Despite the common occurrence and significant impact of persistent pain after breast cancer surgery, limited data have been published on the characteristics and qualities of this pain disorder [16]. Information on the typical clinical presentation such as pain location, pain intensity levels, neuropathic qualities, features of the surgical scar, and analgesic consumption are important as they can aid clinicians in better screening, diagnosing, and managing this chronic pain disorder [17].
Additionally, further data are needed on specific risk factors that may be associated with developing persistent pain after breast cancer surgery. In a study by Gärtner et al. in 2009, which analyzed questionnaires completed by 3754 women 2–3 years after their breast cancer surgery, a 47% prevalence of persistent pain was observed with younger age, adjuvant radiotherapy, and axillary lymph node dissection (ALND) as predictors [18]. A systematic review of 30 studies (19,813 patients) provided further moderate-to-high quality evidence that younger age, radiotherapy, ALND, greater acute postoperative pain, and presence of preoperative pain are associated with persistent pain after breast cancer surgery [19]. However, despite the comprehensive nature of this review, many of the included studies did not explore associations between specific aspects of routine perioperative care, such as surgical or anesthetic-related interventions.
The purpose of this investigation was to identify novel risk factors seldom explored, and corroborate or refute those with previous contradictory findings.

2. Materials and Methods

This was a prospective cohort study that utilized data from a previously completed randomized controlled trial (RCT) (NCT02240199) [20]. This trial sought to evaluate the effects of perioperative pregabalin and intraoperative intravenous (IV) lidocaine infusion on persistent pain after breast cancer surgery. The trial was completed at two Canadian tertiary care centers: Sunnybrook Health Sciences Centre in Toronto, Ontario, and Juravinski Hospital in Hamilton, Ontario, between December 2014 and October 2015. Approval by the Institutional Review Boards at both hospitals (Sunnybrook Health Sciences Centre approval number 270-2014, 24 November 2014; Juravinski Hospital approval number 14-481, 22 July 2014) was granted and informed consent was obtained from each patient prior to enrolment and randomization.

2.1. Eligibility Criteria

Eligibility criteria for the study were women, aged 18–75 years old, who underwent a unilateral or bilateral mastectomy or lumpectomy under general anesthesia, for prophylaxis or belief of isolated cancerous lesions. Exclusions for participation included: breast surgery within the prior 6 months; undergoing a deep inferior epigastric perforator flap procedure; history of chronic pain or a chronic pain syndrome that involved the planned surgical area (axilla, chest, upper arm) and was still relevant in the 3 months preceding surgery; documented hypersensitivity or allergy to pregabalin, gabapentin, or lidocaine; history of ventricular tachycardia, ventricular fibrillation, or atrioventricular block type II or III; congestive heart failure; renal insufficiency (documented creatinine ≥120 mmol/L); known or previously documented cirrhosis; current pregnancy; unable to swallow study medications; surgeon believed the patient was inappropriate for inclusion; unlikely to comply with follow-up (e.g., no fixed address); or language barriers that would impede completion of questionnaires. Additionally, we excluded patients who required gabapentin or pregabalin for another medical condition or who had taken these medications daily during the week before randomization.

2.2. Patient Recruitment and Follow-Up

Patients were approached for study inclusion by screening breast surgeons’ clinic lists, preoperative assessment clinic lists, and operating room booking lists. Eligible patients were invited to voluntarily participate and completed written informed consent. Once consent was obtained, demographics and baseline data were collected (Table 1), including body mass index, ethnicity, marital status, highest education attainment, current employment status, gross household income, smoking status, diabetes, surgery indication, type of procedure, and history of breast cancer. Pain Catastrophizing Scale (PCS) [21] and the Amsterdam Preoperative Anxiety and Information Scale (APAIS) [22] questionnaires were also completed preoperatively by study participants.
Clinical care was provided at the discretion of the attending medical team with only restrictions on the use of any preemptive/preoperative oral analgesics (e.g., preoperative acetaminophen or non-steroidal anti-inflammatories [NSAIDs]), the use of any additional intravenous lidocaine, and the use of any neuraxial or regional anesthetic techniques (except for local wound infiltration by the surgeon, which was restricted to a maximum of 50 mg of bupivacaine). These interventions were not permitted in order to ensure that they would not confound the outcomes.
Research assistants collected data from the intraoperative period using the surgeon’s dictated operative note and the anesthetic record. Patients were followed immediately after surgery in the post-anesthesia care unit to collect postoperative pain and analgesic consumption data. Once patients were discharged from the hospital, they were either called at home by a research assistant or followed up electronically using an electronic data capture system on postoperative days 1, 2, 3, 9, and 3 months after surgery.
Data from the intraoperative period included type of anesthetic (propofol infusion versus volatile anesthetic gas), intraoperative use of ketamine or dexamethasone, use of local anesthetic wound infiltration, type of procedure (mastectomy versus lumpectomy), axillary lymph node dissection, placement of implants or expanders, use of intraoperative fat grafts, peri-areolar surgical incision, and placement of drains. Data in the acute postoperative period included type, amount, and route of opioid consumption, use of NSAIDS (selective COX-2 inhibitors, or acetaminophen), and acute postoperative pain scores (0 to 10 numeric rating scale [NRS]) [23] at rest and with movement (movement defined as 90° abduction of the arm on the ipsilateral surgical side) in the morning and evening on postoperative days 1, 2, 3, and 9.
At 3-months after surgery, patients were assessed for the presence of persistent pain, defined as meeting the following three criteria: (1) any pain at rest or with movement localized to the axilla, arm, shoulder, or chest wall on the side of surgery [24], (2) pain present at 3-month after surgery, and (3) pain was neuropathic in nature based on the Douleur Neuropathique en 4 Interview (DN4-interview) (i.e., one or more of burning, painful cold, or electric shocks, and one or more of tingling, pins and needles, numbness, and itching) [25]. The DN4-interview, developed from the original DN4 questionnaire, consists of 10 yes/no questions thus not relying upon patient physical examination. A cut-off score of 3 indicated neuropathic pain (sensitivity 78.0% and specificity 81.2%).
Three well-researched and validated questionnaires were used to measure health outcomes. Quality of life (QoL) outcomes were evaluated with the Short-Form-36-Health Survey (SF-36), which evaluates a physical component (PCS) and a mental component (MCS) of QoL. A 0–100 scale is used for each domain, with a higher score indicating better outcomes. The PCS incorporates physical function, role physical, bodily pain, and general health, while the MCS evaluates mental health, role emotion, social function, and vitality [26]. The Short Form McGill Pain Questionnaire 2 (SF-MPQ-2) assesses both neuropathic and non-neuropathic pain features, asking patients to rate 22 descriptive items on a 0–10 numerical rating scale (0 = none; 10 = worst possible). These items are a mix of pain characteristics and related symptoms and have been shown to be both reliable and valid specifically in chronic pain patient populations [27]. Lastly, the Brief Pain Inventory (BPI) Short Form is a 9-item questionnaire, which evaluates pain severity, and the interference of this pain on daily functioning [28]. The questionnaire first asks about the current state of pain and then supplies diagrams in which patients identify their areas of pain. Four items about pain intensity (worst pain, least pain, average pain, and current pain) are rated on a 0–10 numerical rating scale (0 = none; 10 = worst possible) generating a pain severity score out of 40, with a higher value indicating more severe pain. There are two items asking about alleviating factors, and one final item on pain interference consisting of seven sub-items (general activity, mood, walking ability, normal walking, relations with other people, sleep, and enjoyment of life). A pain interference score, out of 70, corresponds to these seven sub-items, rated on a 0–10 numerical rating scale (0 = does not interfere; 10 = completely interferes).
Assessment of the patient’s surgical scar was also performed at the 3-month follow-up using the Patient Scar Assessment Scale (PSAS) [29]. This scale evaluates a surgical scar’s painfulness, itchiness, change in color, stiffness, thickness, and irregularity compared to normal skin. A 0–10 point scale was used for evaluation, where 10 was the ‘worst imaginable’ for pain and itchiness, and 10 was ‘very different’ for the difference in color, stiffness, thickness, and irregularity of the scar.

3. Potential Sources of Bias

Since this study is a secondary analysis that included patients enrolled in the primary RCT, we have mitigated many areas of bias by the prospective nature of data collection. Additionally, by using data outcomes that were collected in the RCT prospectively, we significantly reduced the chance of a recall or information bias. Furthermore, by only employing commonly used validated questionnaires, and excluding patients who were likely to provide inaccurate data (due to lack of follow-up or language barriers), we also reduced measurement errors. Certainly, patients who agreed to participate in the RCT represent only a sample of patients at that recruitment site, leading to the possibility of selection bias. A relatively small sample size is also a potential source of bias, increasing the chance of spurious findings. While alpha adjustment is sometimes appropriate (in the case of disjunction testing), this was not relevant in this study, with individual testing performed.

Statistical Analysis

We included all available patient data collected by the trial for this analysis. We grouped patients according to whether they experienced persistent pain 3 months after surgery. Descriptive statistics were calculated for each group and were reported using the mean and standard deviations (SD) of all continuous data, and frequency and percentages for categorical data. Acute pain scores at rest and movement were averaged over the first three postoperative days.
We performed univariate testing to compare preoperative, intraoperative, and postoperative variables between those with and without persistent pain using a t-test for continuous variables or a chi-square test for categorical and dichotomous variables. In developing the multivariable logistic regression model for an adjusted analysis, the number of variables included in the model was limited to the number of events of persistent pain using the commonly employed rule-of-thumb of 10 events for every variable included. Thus, given that 53 patients reported pain in the prior trial, we limited the number of variables in the adjusted analysis to five variables. This limitation in the number of variables was performed to ensure model stability and reduce over-fitting [30]. We constructed separate models to identify preoperative, intraoperative, and postoperative predictors. Variables were chosen for inclusion in the regression model by first including those that were significant in the univariate analysis followed by those with p-values close to 0.05 up to our limit of five variables, as described. The dependent variable in the logistic regression model was the presence of persistent pain at 3 months, and selected independent variables were included in the model using forced-simultaneous entry. We tested for collinearity using the variance inflation factor (VIF), and if two variables were highly correlated (VIF >5) the least significant variable (lower coefficient) was dropped from the model. The goodness-of-fit of the logistic regression models was assessed using the Hosmer–Lemeshow test [31]. All statistical analyses were performed using SPSS (version 23, IBM, Armonk, NY, USA). All tests were two-sided and p < 0.05 was considered statistically significant.

4. Results

From the initial group of 296 eligible patients, 165 patients declined participation and 31 were not identified preoperatively from the initial group of 296 eligible patients. A total of 100 patients undergoing breast cancer surgery were enrolled in the study and included in this analysis, of which 53 had persistent pain, and 47 had no pain (Figure 2).
Included patients were women with an average age of 54.8 years (SD 11.0), primarily of European descent (89%), non-smokers (71%), and non-diabetic (93%) (Table 1). Approximately 77% of patients were married or in common law relationships, 69% held a university or college degree, 68% were employed, and 40% had a household income of greater than $100,000 CAD.
The majority of patients underwent a unilateral lumpectomy (75%), followed by a unilateral mastectomy (18%), bilateral mastectomy (6%), and bilateral lumpectomy (1%) (Table 1). In 94% of patients, breast cancer or a suspected cancerous lesion was the indication for surgery, while only 6% of patients underwent prophylactic surgery (i.e., family history or presence of BRCA gene).

4.1. Characteristics of Persistent Pain after Breast Cancer Surgery

At the 3-month follow-up, 53 (53%) patients reported persistent pain after their surgery. Among patients with persistent pain, the average worst pain reported was 2.5 (SD 2.4) on a scale of 0 to 10, with 41 (77.4%), 8 (15.1%), and 4 (7.5%) patients reporting mild (NRS 0–3), moderate (NRS 4–7), and severe (NRS 8–10) pain at rest, respectively (Table 2). During movement, the average worst pain score was 2.8 (SD 2.8), with 37 (69.8%) mild, 11 (15.1%) moderate, and 5 (9.4%) patients experiencing severe pain. Patients with persistent pain also reported an average of 3.5 days (SD 2.5) of pain in the week prior to evaluation (Table 2). Furthermore, approximately 60% of patients reported pain in the axilla, 45% in the chest, 17% in the shoulders, 15% in the arms, and 6% in their hands. Additionally, 36% of patients with persistent pain reported a reduced range of motion in their elbows or shoulders at follow-up.
Patients with persistent pain were evaluated on characteristics of neuropathic pain. Fifty-one patients (96.2% of those reporting persistent pain) had pain with neuropathic features according to the DN-4 (≥3 positive answers). The most common neuropathic features were numbness (58.5%) and tingling (41.5%) (Table 2).
The surgical scar, assessed by the PSAS, indicated that patients with persistent pain reported a significantly higher score on the scar’s painfulness (1.8 versus 1.3, p = 0.025), itchiness (2.0 versus 1.2, p = 0.001), the difference in color compared to normal skin (5.2 versus 3.7, p = 0.018), and irregularity (4.2 versus 2.7, p = 0.010) (Table 3).
Patients with persistent pain also scored significantly worse on the SF-MPQ-2 overall than patients who reported no pain (p < 0.001) (Table 3). Similarly, patients with persistent pain reported significantly worse pain interference overall (BPI Interference scores: 3.1 versus 1.6, p = 0.001) and on specific activities: general activities (p = 0.02); mood (p = 0.001); walking ability (p = 0.006); normal work (p = 0.001); relations with others (p = 0.016); sleep (p < 0.001) and enjoyment of life (p = 0.003). Patients with persistent pain also reported worse quality of life scores on both the SF-36 physical (24.0 versus 27.1, p = 0.004) and mental components (70.1 versus 85.3, p = 0.004).
With respect to persistent analgesic use at 3 months after surgery, 7.5% (four patients) of those with persistent pain reported using opioids for the management of their surgical pain compared to only 2.1% (one patient) without persistent pain (p = 0.367). Acetaminophen with codeine had the highest use at 5.7%, followed by hydromorphone at 1.9%. Non-opioid medication was used by 13 (24.5%) patients for incisional pain at the 3-month follow-up compared to three (6.4%) patients without persistent pain (p = 0.015). For non-opioid analgesics, acetaminophen had the greatest use at 13.2%, followed by NSAIDs at 5.7%, and gabapentin at 3.8% (Table 3).

4.2. Univariate Analysis

In the univariate analysis of preoperative variables, being employed at the time of surgery (p = 0.027), and higher preoperative scores on both the Pain Catastrophizing Scale (p = 0.005) and Amsterdam Preoperative Anxiety and Information Scale (p = 0.013) were significantly associated with persistent pain at 3-months (Table 4).
Analysis of intraoperative variables indicated that only IV administration of dexamethasone (p = 0.044) was associated with persistent pain (Table 5).
In univariate analyses of postoperative variables, higher mean pain scores at rest (mean 2.2 [SD 1.52], p = 0.001) and movement (mean 3.4 [SD 1.96], p = 0.013) during the first 3 days after surgery, and adjuvant chemotherapy, were associated with persistent pain (Table 6).

4.3. Adjusted Analysis

Variables in the logistic regression model for preoperative risk factors included diabetes, age, employment status, and PCS and APAIS scores. Employment status was the only significant predictor associated with persistent pain (OR 2.70, 95% CI 1.04 to 9.66, p = 0.042) (Table 7). Variables in the intraoperative model included surgery duration, type of surgery, propofol infusion, ketamine, and dexamethasone use, of which none were significant predictors. In the postoperative model, variables included were mean acute postoperative pain scores at rest and at movement, as well as postoperative use of opioids and acetaminophen, and adjuvant chemotherapy. Higher postoperative mean pain scores on movement (OR 1.63, 95% CI 1.06 to 2.51, p = 0.027) and adjuvant chemotherapy (OR 3.30, 95% CI 1.19 to 9.15, p = 0.022) were independent predictors of persistent pain.

5. Discussion

In this study of 100 patients undergoing breast cancer surgery, our data suggest that persistent pain is an exceedingly common complication, is mild-moderate in intensity, primarily exists in the axilla and chest, has neuropathic pain features, is associated with interference across all domains of daily living, worse quality of life, and increases the need for non-opioid analgesics. Our univariate analysis suggests that employment status, pain catastrophizing, preoperative anxiety, use of intraoperative IV dexamethasone, higher postoperative pain scores, and adjuvant chemotherapy may be associated with persistent pain at 3 months after surgery. Findings of our adjusted analyses identified employment status, worse postoperative pain on movement, and adjuvant chemotherapy as independent predictors of persistent pain.
There are several strengths to this analysis. Given that our analysis utilized data from a previously completed randomized controlled trial, data were prospectively collected and avoided the typical issues with case-control studies such as recall bias and missing data. Furthermore, our study collected specific anesthetic and surgical-related factors that have not been previously explored as potential risk factors for persistent pain after surgery. Lastly, our study obtained a notable follow-up rate of 100% at 3 months, allowing greater outcome data for our analyses and avoiding bias caused by loss to follow-up.
Our study also contributes novel insights to our understanding of persistent pain after breast cancer surgery. Our data suggest that patients who are employed at the time of surgery may be more likely to develop persistent pain. This is an interesting and novel finding and only a few perioperative studies have sought to evaluate this relationship [32,33,34]. A retrospective survey of 408 patients who underwent breast cancer surgery also found that employment status at the time of surgery was significantly associated with the development of persistent post-surgical pain [32]. Further, a study of 226 patients who underwent open inguinal hernia repair also reported that those who had full-time employment at the time of surgery were more likely to suffer from chronic pain [33]. The mechanism responsible for this relationship is not readily apparent. Outside the perioperative period, work-related stress and high psychological demands have been identified as risk factors for chronic pain [35]. For those who are employed at the time of surgery, similar stressors may exist such as stress related to taking time off work, uncertainty surrounding their return-to-work date, the possibility of job loss, returning to work too soon, and financial strains of missing work. The added work-related stress may be an important contribution to the development of chronic post-surgical pain, and future studies will be needed to further evaluate this association.
Additionally, our data suggest that acute pain scores (i.e., in the 3 days following surgery), specifically on movement, are positively associated with developing persistent pain. This finding is also consistent with prior data in patients undergoing breast cancer [19] and non-breast cancer-related surgeries [36]. Movement-evoked pain after surgery has been shown to be a strong predictor of chronic post-surgical pain, and even greater than acute pain scores at rest [36]. The mechanism for the development of persistent postsurgical pain is complex and involves various molecular and cellular changes in the peripheral and central nervous systems. Inflammation [37] and nerve injury result in long-term synaptic plasticity that amplifies pain signaling, also known as pain sensitization [38]. Animal studies have assisted in identifying the neurobiological mechanism of pain sensitization after surgery, including the role of specific receptors, mediators, and neurotransmitters involved [39]. On a molecular level, when peripheral nerves are damaged, there are changes within sensory nerves that involve substance P, calcitonin gene-related peptide, and particularly, the upregulation of sodium channels [40], specifically Nav1.3 which is an embryonic voltage-gated sodium channel that has fast-activating and fast-inactivating current [41]. These changes result in spontaneous ectopic discharges (resting pain) and greater sensitivity to discharge (i.e., decreased activation threshold and increased amplitude of pain response [42]). Inflammation and nerve injury induces transcriptional changes in the dorsal horn, strengthening the offending neural pathway, and resulting in greater neuroplastic changes in the central and peripheral nervous system, resulting in persistent pain [43]. Nonetheless, while acute pain intensities may be associated with persistent pain [44], prior trials aimed at improving postoperative pain intensities have not consistently demonstrated a reduction in the development of chronic pain [45]. This may be in part related to statistical power, and thus larger trials in this area are needed.
Another predictor of persistent pain identified in our univariable and multivariable models is adjuvant chemotherapy. This finding is highly controversial, with contradicting reports in the literature [9,19,46,47,48,49]. Nevertheless, adjuvant chemotherapy as a significant risk factor for persistent pain should be the focus of future large prospective studies, as perhaps a better balance between its advantage of improved disease-free duration and risk of persistent pain may be achieved. While dexamethasone was associated with persistent pain in the univariate analysis, significance was lost in the adjusted analysis. Several studies document a beneficial effect of perioperative dexamethasone use and acute analgesic outcomes (pain intensities and opioid consumption), but few studies have demonstrated an effect on persistent pain [50]. A secondary analysis of 310 patients who underwent breast cancer surgery also reported a non-significant difference in the incidence of chronic pain between those who received and those who did not receive dexamethasone [51]. Further, an analysis of 1043 cardiac surgical patients also found no association between steroid use around the time of surgery and the development of persistent pain [52].
Our data provide additional insights into the characteristics of persistent pain after surgery. Our analysis suggests that there are unique characteristics of the surgical scar in those with persistent pain. Specifically, patients with pain report changes in the color and contour of their scars compared to those without pain. Furthermore, consistent with prior studies, our data suggest that persistent pain after breast cancer surgery is largely a neuropathic pain disorder. The vast majority of patients with persistent pain reported a neuropathic feature such as burning, shooting, numbness, and tingling pain, and possibly allodynia and hyperalgesia [14,53]. The high prevalence of neuropathic features suggests that perioperative peripheral nerve injury may be a key component in the pathogenesis of this pain disorder. It also suggests that a neuropathic pain approach could be considered in the management of persistent pain after breast cancer surgery through the use of pain medications [54,55], targeted nerve blocks [56,57], or even neuromodulation [58,59]. A recently published review of studies assessed various treatment modalities for chronic pain after breast cancer surgery, including physical and psychological approaches as well as pharmacological (e.g., anti-depressants, anti-convulsants, topical analgesic creams) and interventional strategies (e.g., PEC I or II blocks, serratus plane blocks, neuromodulation). However, high-quality evidence of beneficial interventions is lacking, stressing the need to identify novel treatments and, more importantly, find ways to prevent this type of pain from occurring [16,60,61].
There are several limitations to our investigation. First and foremost, this study included a relatively small sample size of 100 patients, which restricted both the number of variables that could be included in a multivariable model, as well as limiting our statistical power to identify possible relationships. Our small sample size also increased our chances of spurious findings. Second, while there are benefits of using secondary data, the primary trial was not designed for this exploratory analysis and thus many perioperative factors that may have been worthwhile collecting were not recorded. Third, given that patients were only assessed 3 months after surgery, we do not know if our findings are also predictive of pain at a much longer follow-up period after surgery (i.e., 1 year). However, previously published data suggest that this pain may persist for years to follow [18]. Furthermore, while the prospective nature of this study, together with a 100% response rate to the study questionnaires, makes it less prone to several sources of bias, a selection bias may have occurred since patients in this cohort were only those who agreed to participate in the randomized controlled trial at the participating centers. Prospective data collection also does not eliminate information bias and measurement errors, although our use of validated questionnaires probably mitigated this risk. Lastly, we conducted many statistical tests both in our univariate and multivariate analysis, which raises the possibility of spurious findings by chance.
While ongoing efforts are aimed at prolonging life for patients with cancer, it is also important that resources be directed at improving the quality of life for these survivors. Persistent pain after breast cancer surgery is a detrimental yet common complication, which should be addressed preemptively. While this exploratory analysis provides both confirmatory and novel findings, larger studies are needed to verify these predictive factors, and whether interventions modifying these factors could indeed adjust the risk of developing persistent pain.

Author Contributions

Conceptualization, J.S.K., S.S. and R.P.; methodology, J.S.K., S.S., R.P. and L.W.; validation, J.S.K., S.S., R.P. and L.W.; formal analysis, J.S.K., R.P. and L.W.; investigation, J.S.K., S.S. and R.P.; resources, J.S.K. and S.S.; data curation, J.S.K.; writing—original draft preparation, S.S., R.P., E.D., J.S.K., S.M. and L.W.; writing—review and editing, S.S., E.D., J.S.K., R.P., S.M. and L.W., project administration, S.S. and J.S.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no funding.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the ethics review boards at Sunnybrook Health Sciences Centre (approval date - November 24, 2014. Project ID Number: 270-2014) and Juravinski Hospital (approval date - July 22, 2014. Project ID Number: 14-481). Prior to patient enrollment, the original interventional trial was registered at clinicaltrials.gov (NCT02240199).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data is contained within the article.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Siegel, R.L.; Miller, K.D.; Wagle, N.S.; Jemal, A. Cancer Statistics. CA Cancer J. Clin. 2023, 73, 17–48. [Google Scholar] [CrossRef] [PubMed]
  2. Ma, J.; Jemal, A. Breast Cancer Statistics. In Breast Cancer Metastasis and Drug Resistance; Springer: New York, NY, USA, 2013. [Google Scholar]
  3. Miller, K.D.; Nogueira, L.; Mariotto, A.B.; Rowland, J.H.; Yabroff, K.R.; Alfano, C.M.; Kramer, J.L.; Siegel, R.L. Cancer Treatment and Survivorship Statistics. CA Cancer J. Clin. 2019, 69, 363–385. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Bray, F.; Ferlay, J.; Soerjomataram, I.; Siegel, R.L.; Torre, L.A.; Jemal, A. Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2018, 68, 394–424. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Siegel, R.L.; Miller, K.D.; Jemal, A. Cancer Statistics. CA Cancer J. Clin. 2019, 69, 7–34. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Schug, S.A.; Lavand’homme, P.; Barke, A.; Korwisi, B.; Rief, W.; Treede, R.-D. The IASP Classification of Chronic Pain for ICD-11: Chronic Postsurgical or Posttraumatic Pain. Pain 2019, 160, 45–52. [Google Scholar] [CrossRef]
  7. Wang, L.; Devasenapathy, N.; Hong, B.Y.; Cohen, J.; Kheyson, S.; Oparin, Y.; Kennedy, S.A.; Romerosa, B.; Arora, N.; Kwon, H.; et al. Prevalence and Intensity of Persistent Post-Surgical Pain following Breast Cancer Surgery: A Systematic Review and Meta-Analysis of Observational Studies. Br. J. Anaesth. 2020, 125, 346–357. [Google Scholar] [CrossRef]
  8. Wijayasinghe, N.; Andersen, K.G.; Kehlet, H. Neural Blockade for Persistent Pain After Breast Cancer Surgery. Reg. Anesth. Pain Med. 2014, 39, 272–278. [Google Scholar] [CrossRef]
  9. Macdonald, L.; Bruce, J.; Scott, N.W.; Smith, W.C.S.; Chambers, W.A. Long-Term Follow-Up of Breast Cancer Survivors with Post-Mastectomy Pain Syndrome. Br. J. Cancer 2005, 92, 225–230. [Google Scholar] [CrossRef] [Green Version]
  10. Gottrup, H.; Andersen, J.; Arendt-Nielsen, L.; Jensen, T.S. Psychophysical Examination in Patients with Post-Mastectomy Pain. Pain 2000, 87, 275–284. [Google Scholar] [CrossRef]
  11. Caffo, O.; Amichetti, M.; Ferro, A.; Lucenti, A.; Valduga, F.; Galligioni, E. Pain and Quality of Life after Surgery for Breast Cancer. Breast Cancer Res. Treat. 2003, 80, 39–48. [Google Scholar] [CrossRef]
  12. Bishop, S.R.; Warr, D. Coping, Catastrophizing and Chronic Pain in Breast Cancer. J Behav. Med. 2003, 26, 265–281. [Google Scholar] [CrossRef]
  13. Belfer, I.; Schreiber, K.L.; Shaffer, J.R.; Shnol, H.; Blaney, K.; Morando, A.; Englert, D.; Greco, C.; Brufsky, A.; Ahrendt, G.; et al. Persistent Postmastectomy Pain in Breast Cancer Survivors: Analysis of Clinical, Demographic, and Psychosocial Factors. J Pain. 2013, 14, 1185–1195. [Google Scholar] [CrossRef]
  14. Jung, B.F.; Ahrendt, G.M.; Oaklander, A.L.; Dworkin, R.H. Neuropathic Pain Following Breast Cancer Surgery: Proposed Classification and Research Update. Pain 2003, 104, 1–13. [Google Scholar] [CrossRef]
  15. Visnjevac, O.; Matson, B. Postmastectomy Pain Syndrome: An Unrecognized Annual Billion Dollar National Financial Burden. J. Pain 2013, 14, S33. [Google Scholar] [CrossRef]
  16. Khan, J.S.; Ladha, K.S.; Abdallah, F.; Clarke, H. Treating Persistent Pain After Breast Cancer Surgery. Drugs 2020, 80, 23–31. [Google Scholar] [CrossRef]
  17. Chang, P.J.; Asher, A.; Smith, S.R. A Targeted Approach to Post-Mastectomy Pain and Persistent Pain Following Breast Cancer Treatment. Cancers 2021, 13, 5191. [Google Scholar] [CrossRef]
  18. Gärtner, R.; Jensen, M.-B.; Nielsen, J.; Ewertz, M.; Kroman, N.; Kehlet, H. Prevalence of and Factors Associated with Persistent Pain Following Breast Cancer Surgery. JAMA 2009, 302, 1985–1992. [Google Scholar] [CrossRef] [Green Version]
  19. Wang, L.; Guyatt, G.H.; Kennedy, S.A.; Romerosa, B.; Kwon, H.Y.; Kaushal, A.; Chang, Y.; Craigie, S.; de Almeida, C.P.; Couban, R.J.; et al. Predictors of Persistent Pain After Breast Cancer Surgery: A Systematic Review and Meta-Analysis of Observational Studies. CMAJ 2016, 188, E352–E361. [Google Scholar] [CrossRef] [Green Version]
  20. Khan, J.S.; Hodgson, N.; Choi, S.; Reid, S.; Paul, J.E.; Hong, N.J.L.; Holloway, C.; Busse, J.W.; Gilron, I.; Buckley, D.N.; et al. Perioperative Pregabalin and Intraoperative Lidocaine Infusion to Reduce Persistent Neuropathic Pain After Breast Cancer Surgery: A Multicenter, Factorial, Randomized, Controlled Pilot Trial. J. Pain 2019, 20, 980–993. [Google Scholar] [CrossRef]
  21. Sullivan, M.J.L.; Bishop, S.R.; Pivik, J. The Pain Catastrophizing Scale: Development and Validation. Psychol. Assess. 1995, 7, 524–532. [Google Scholar] [CrossRef]
  22. Moerman, N.; van Dam, F.S.; Muller, M.J.; Oosting, H. The Amsterdam Preoperative Anxiety and Information Scale (APAIS). Anesth. Analg. 1996, 82, 445–451. [Google Scholar] [PubMed]
  23. Hawker, G.A.; Mian, S.; Kendzerska, T.; French, M. Measures of Adult Pain: Visual Analog Scale for Pain (VAS Pain), Numeric Rating Scale for Pain (NRS Pain), McGill Pain Questionnaire (MPQ), Short-Form McGill Pain Questionnaire (SF-MPQ), Chronic Pain Grade Scale (CPGS), Short Form-36 Bodily Pain Scale (SF-36 BPS), and Measure of Intermittent and Constant Osteoarthritis Pain (ICOAP). Arthritis Care Res. 2011, 63, S240–S252. [Google Scholar] [CrossRef] [PubMed]
  24. Forget, P.; Sitter, T.M.; Hollick, R.J.; Dixon, D.; van Maanen, A.; Dekleermaker, A.; Duhoux, F.P.; De Kock, M.; Berliere, M.; KBCt Group. Characterization of Preoperative, Postsurgical, Acute and Chronic Pain in High Risk Breast Cancer Patients. J. Clin. Med. 2020, 9, 3831. [Google Scholar] [CrossRef] [PubMed]
  25. Bouhassira, D.; Attal, N.; Alchaar, H.; Boureau, F.; Brochet, B.; Bruxelle, J.; Cunin, G.; Fermanian, J.; Ginies, P.; Grun-Overdyking, A.; et al. Comparison of Pain Syndromes Associated with Nervous or Somatic Lesions and Development of a New Neuropathic Pain Diagnostic Questionnaire (DN4). Pain 2005, 114, 29–36. [Google Scholar] [CrossRef]
  26. Ware, J.E., Jr.; Sherbourne, C.D. The MOS 36-ltem Short-Form Health Survey (SF-36). Med. Care. 1992, 30, 473–483. [Google Scholar] [CrossRef]
  27. Dworkin, R.H.; Turk, D.C.; Revicki, D.A.; Harding, G.; Coyne, K.S.; Peirce-Sandner, S.; Bhagwat, D.; Everton, D.; Burke, L.B.; Cowan, P.; et al. Development and Initial Validation of an Expanded and Revised Version of the Short-Form McGill PAIN Questionnaire (SF-MPQ-2). Pain 2009, 144, 35–42. [Google Scholar] [CrossRef]
  28. Poquet, N.; Lin, C. The Brief Pain Inventory (BPI). J. Physiother. 2016, 62, 52. [Google Scholar] [CrossRef] [Green Version]
  29. Draaijers, L.J.; Tempelman, F.R.H.; Botman, Y.A.M.; Tuinebreijer, W.E.; Middelkoop, E.; Kreis, R.W.; Van Zuijlen, P.P. The Patient and Observer Scar Assessment Scale: A Reliable and Feasible Tool for Scar Evaluation. Plast. Reconstr. Surg. 2004, 113, 1960–1965. [Google Scholar] [CrossRef]
  30. Peduzzi, P.; Concato, J.; Kemper, E.; Holford, T.R.; Feinstein, A.R. A Simulation Study of the Number of Events Per Variable in Logistic Regression Analysis. J. Clin. Epidemiol. 1996, 49, 1373–1379. [Google Scholar] [CrossRef]
  31. Steyerberg, E.W. Applications of Prediction Models. In Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating; Springer: New York, NY, USA, 2009. [Google Scholar]
  32. Smith, C.S.; Bourne, D.; Squair, J.; Phillips, D.O.; Chambers, A.W. A Retrospective Cohort Study of Post Mastectomy Pain Syndrome. Pain 1999, 83, 91–95. [Google Scholar] [CrossRef]
  33. Poobalan, A.S.; Bruce, J.; King, P.M.; Chambers, W.A.; Krukowski, Z.H.; Smith, W.C.S. Chronic Pain and Quality of Life Following Open Inguinal Hernia Repair. Br. J. Surg. 2001, 88, 1122–1126. [Google Scholar] [CrossRef]
  34. Hah, J.M.; Cramer, E.; Hilmoe, H.; Schmidt, P.; McCue, R.; Trafton, J.; Clay, D.; Sharifzadeh, Y.; Ruchelli, G.; Goodman, S. Factors Associated with Acute Pain Estimation, Postoperative Pain Resolution, Opioid Cessation, and Recovery: Secondary Analysis of a Randomized Clinical Trial. JAMA Netw. Open 2019, 2, e190168. [Google Scholar] [CrossRef] [Green Version]
  35. Kopec, J.A.; Sayre, E.C. Work-Related Psychosocial Factors and Chronic Pain: A Prospective Cohort Study in Canadian workers. J. Occup. Environ. Med. 2004, 46, 1263–1271. [Google Scholar]
  36. Gilron, I.; Vandenkerkhof, E.; Katz, J.; Kehlet, H.; Carley, M. Evaluating the Association Between Acute and Chronic Pain After Surgery: Impact of Pain Measurement Methods. Clin. J. Pain 2017, 33, 588–594. [Google Scholar] [CrossRef]
  37. Calapai, M.; Puzzo, L.; Bova, G.; Vecchio, D.A.; Blandino, R.; Barbagallo, A.; Ammendolia, I.; Cardia, L.; De Pasquale, M.; Calapai, F.; et al. Effects of Physical Exercise and Motor Activity on Oxidative Stress and Inflammation in Post-Mastectomy Pain Syndrome. Antioxidants 2023, 12, 643. [Google Scholar] [CrossRef]
  38. Richebé, P.; Capdevila, X.; Rivat, C. Persistent Postsurgical Pain: Pathophysiology and Preventative Pharmacologic Considerations. Anesthesiology. 2018, 129, 590–607. [Google Scholar] [CrossRef]
  39. Pogatzki-Zahn, E.M.; Segelcke, D.; Schug, S.A. Postoperative pain—From mechanisms to treatment. PAIN Rep. 2017, 2, e588. [Google Scholar] [CrossRef]
  40. Woolf, C.J.; Salter, M.W. Neuronal Plasticity: Increasing the Gain in Pain. Science 2000, 288, 1765–1768. [Google Scholar] [CrossRef]
  41. Lai, J.; Hunter, J.C.; Porreca, F. The Role of Voltage-Gated Sodium Channels in Neuropathic Pain. Curr. Opin. Neurobiol. 2003, 13, 291–297. [Google Scholar] [CrossRef]
  42. Devor, M.; Seltzer, Z. Pathophysiology of Damaged Nerves in Relation to Chronic Pain. In Textbook of Pain; Churchill Livingstone: London, UK, 1999; pp. 129–164. [Google Scholar]
  43. Latremoliere, A.; Woolf, C.J. Central Sensitization: A Generator of Pain Hypersensitivity by Central Neural Plasticity. J. Pain 2009, 10, 895–926. [Google Scholar] [CrossRef] [Green Version]
  44. Tait, R.C.; Zoberi, K.; Ferguson, M.; Levenhagen, K.; Luebbert, R.A.; Rowland, K.; Salsich, G.B.; Herndon, C. Persistent Post-Mastectomy Pain: Risk Factors and Current Approaches to Treatment. J. Pain 2018, 19, 1367–1383. [Google Scholar] [CrossRef] [PubMed]
  45. Carley, M.E.; Chaparro, L.E.; Choinière, M.; Kehlet, H.; Moore, R.A.; Kerkhof, E.V.D.; Gilron, I. Pharmacotherapy for the Prevention of Chronic Pain after Surgery in Adults: An Updated Systematic Review and Meta-analysis. Anesthesiology 2021, 135, 304–325. [Google Scholar] [CrossRef] [PubMed]
  46. Tasmuth, T.; Von Smitten, K.; Hietanen, P.; Kataja, M.; Kalso, E. Pain and Other Symptoms After Different Treatment Modalities of Breast Cancer. Ann. Oncol. 1995, 6, 453–459. [Google Scholar] [CrossRef] [PubMed]
  47. Macrae, W.A. Chronic Post-Surgical Pain: 10 years on. Br. J. Anaesth. 2008, 101, 77–86. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  48. Carpenter, J.S.; Sloan, P.; Andrykowski, M.A.; McGrath, P.; Sloan, D.; Rexford, T.; Kenady, D. Risk Factors for Pain After Mastectomy/Lumpectomy. Cancer Pract. 1999, 7, 66–70. [Google Scholar] [CrossRef]
  49. Poleshuck, E.L.; Katz, J.; Andrus, C.H.; Hogan, L.A.; Jung, B.F.; Kulick, D.I.; Dworkin, R.H. Risk Factors for Chronic Pain Following Breast Cancer Surgery: A Prospective Study. J. Pain 2006, 7, 626–634. [Google Scholar] [CrossRef]
  50. Oliveira, D.; Almeida, G.S.; Benzon, M.D.; Mccarthy, H.T. Perioperative Single Dose Systemic Dexamethasone for Postoperative Pain. Anesthesiology 2011, 115, 575–588. [Google Scholar] [CrossRef] [Green Version]
  51. De Oliveira, G.S., Jr.; Bialek, J.M.; Turan, A.; McCarthy, R.J.; Sessler, D.I. Perioperative Dexamethasone and the Development of Chronic Postmastectomy Pain. Reg. Anesth. Pain Med. 2015, 40, 539–544. [Google Scholar] [CrossRef] [Green Version]
  52. Turan, A.; Belley-Cote, E.P.; Vincent, J.; Sessler, D.I.; Devereaux, P.J.; Yusuf, S.; van Oostveen, R.; Cordova, G.; Yared, J.-P.; Yu, H.; et al. Methylprednisolone Does Not Reduce Persistent Pain after Cardiac Surgery. Anesthesiology 2015, 123, 1404–1410. [Google Scholar] [CrossRef] [Green Version]
  53. Andersen, K.G.; Kehlet, H. Persistent Pain After Breast Cancer Treatment: A Critical Review of Risk Factors and Strategies for Prevention. J. Pain 2011, 12, 725–746. [Google Scholar] [CrossRef]
  54. Eija, K.; Tiina, T. Amitriptyline Effectively Relieves Neuropathic Pain Following Treatment Of Breast Cancer. Pain 1996, 64, 293–302. [Google Scholar] [CrossRef]
  55. Finnerup, N.B.; Attal, N.; Haroutounian, S.; McNicol, E.; Baron, R.; Dworkin, R.H.; Gilron, I.; Haanpää, M.; Hansson, P.; Jensen, T.S.; et al. Pharmacotherapy for Neuropathic Pain in Adults: A Systematic Review and Meta-Analysis. Lancet Neurol. 2015, 14, 162–173. [Google Scholar] [CrossRef] [Green Version]
  56. Kairaluoma, P.M.; Bachmann, M.S.; Rosenberg, P.H.; Pere, P.J. Preincisional Paravertebral Block Reduces the Prevalence of Chronic Pain After Breast Surgery. Anesth. Analg. 2006, 103, 703–708. [Google Scholar] [CrossRef]
  57. Zocca, J.A.; Chen, G.H.; Puttanniah, V.G.; Hung, J.C.; Gulati, A. Ultrasound-Guided Serratus Plane Block for Treatment of Postmastectomy Pain Syndromes in Breast Cancer Patients: A Case Series. Pain Pract. 2016, 17, 141–146. [Google Scholar] [CrossRef]
  58. Silva, J.G.; Santana, C.G.; Inocêncio, K.R.; Orsini, M.; Machado, S.; Bergmann, A. Electrocortical Analysis of Patients with Intercostobrachial Pain Treated with TENS after Breast Cancer Surgery. J. Phys. Ther. Sci. 2014, 26, 349–353. [Google Scholar] [CrossRef] [Green Version]
  59. Mainkar, O.; Solla, C.A.; Chen, G.; Legler, A.; Gulati, A. Pilot Study in Temporary Peripheral Nerve Stimulation in Oncologic Pain. Neuromodulation Technol. Neural Interface 2020, 23, 819–826. [Google Scholar] [CrossRef] [Green Version]
  60. Calapai, M.; Esposito, E.; Puzzo, L.; Vecchio, D.A.; Blandino, R.; Bova, G.; Quattrone, D.; Mannucci, C.; Ammendolia, I.; Mondello, C.; et al. Post-Mastectomy Pain: An Updated Overview on Risk Factors, Predictors, and Markers. Life 2021, 11, 1026. [Google Scholar] [CrossRef]
  61. Capuco, A.; Urits, I.; Orhurhu, V.; Chun, R.; Shukla, B.; Burke, M.; Kaye, R.J.; Garcia, A.J.; Kaye, A.D.; Viswanath, O. A Comprehensive Review of the Diagnosis, Treatment, and Management of Postmastectomy Pain Syndrome. Curr. Pain Headache Rep. 2020, 24, 1–12. [Google Scholar] [CrossRef]
Surgeries 04 00031 g001 550
Figure 1. Peripheral nerves innervating the breast. Obtained with permission from Dr. Nelun Wijayasinghe from article [8]. Innervation of the breast and location of the nerves at risk during breast cancer surgery. ICBN indicates intercostobrachial nerve (sensory only); II-VI, intercostal nerves 2 to 6, lateral cutaneous branches (sensory only); LPN, lateral pectoral nerve (mixed sensory and motor); LTN, long thoracic nerve (motor only); MCN, medial cutaneous nerve of the arm (sensory only); MPN, medial pectoral nerve (mixed sensory and motor); TDN, thoracodorsal nerve (motor only).
Figure 1. Peripheral nerves innervating the breast. Obtained with permission from Dr. Nelun Wijayasinghe from article [8]. Innervation of the breast and location of the nerves at risk during breast cancer surgery. ICBN indicates intercostobrachial nerve (sensory only); II-VI, intercostal nerves 2 to 6, lateral cutaneous branches (sensory only); LPN, lateral pectoral nerve (mixed sensory and motor); LTN, long thoracic nerve (motor only); MCN, medial cutaneous nerve of the arm (sensory only); MPN, medial pectoral nerve (mixed sensory and motor); TDN, thoracodorsal nerve (motor only).
Surgeries 04 00031 g001
Surgeries 04 00031 g002 550
Figure 2. Patient flow study diagram.
Figure 2. Patient flow study diagram.
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Table
Table 1. Baseline characteristics of included patients.
Table 1. Baseline characteristics of included patients.
Characteristicsn (%)/Mean (SD)
All Patients (n = 100)No Pain (n = 47)Persistent Pain (n = 53)
Age54.8 (11.0)55.9 (11.2)53.9 (10.9)
Sex (female)100 (100%)47 (100%)53 (100%)
Reason for surgery
Breast cancer or belief of cancerous lesions94 (94.0)44 (93.6)50 (94.3)
Prophylactic surgery6 (6.0)3 (6.4)3 (5.7)
Type of procedure
Unilateral lumpectomy75 (75.0)38 (80.9)37 (69.8)
Bilateral lumpectomy1 (1.0)0 (0.0)1 (1.9)
Unilateral mastectomy18 (18.0)8 (17.0)10 (18.9)
Bilateral mastectomy6 (6.0)1 (2.1)5 (9.4)
Prior breast cancer10 (10)5 (10.6)5 (9.4)
Table
Table 2. Characteristics of persistent pain at 3 months after surgery among patients with persistent pain (n = 53).
Table 2. Characteristics of persistent pain at 3 months after surgery among patients with persistent pain (n = 53).
Characteristics
Pain score at rest, mean (SD) *2.5 (2.4)
Pain score at rest severity, n (%)
Mild41 (77.4)
Moderate8 (15.1)
Severe4 (7.5)
Pain score on movement, mean (SD)2.8 (2.8)
Pain score on movement severity, n (%)
Mild37 (69.8)
Moderate11 (15.1)
Severe5 (9.4)
Days with pain in prior week, mean (SD) δ3.5 (2.5)
Locations of pain, n (%)
Axilla32 (60.4)
Hand3 (5.7)
Chest24 (45.3)
Shoulder9 (17.0)
Arm8 (15.1)
Medial arm3 (5.7)
Lateral arm5 (9.4)
Neuropathic pain(≥3 positive answers on the DN-4), n (%)51 (96.2)
Burning18 (34.0)
Painful cold3 (5.7)
Electric shock16 (30.2)
Tingling22 (41.5)
Pins and needles19 (35.8)
Numbness31 (58.5)
Itching21 (39.6)
* Pain scores represent worst possible pain in the last week δ Days with pain represent number of days the patient experienced pain in the last week.
Table
Table 3. Post-operative variables in patients with and without persistent pain at 3 months after surgery.
Table 3. Post-operative variables in patients with and without persistent pain at 3 months after surgery.
CharacteristicsNo Pain (n = 47)Persistent Pain (n = 53)p-Value
SF-MPQ-2 Total Score, mean (SD)1.2 (0.5)2.2 (1.3)<0.001 *
SF-36 PCS score, mean (SD)27.1 (4.5)24.0 (5.6)0.004 *
SF-36 MCS score, mean (SD)85.3 (22.7)70.1 (27.9)0.004 *
BPI Pain Interference, mean (SD)1.6 (1.7)3.1 (2.6)0.001 *
General activity, mean (SD)1.7 (2.3)2.9 (2.9)0.020 *
Mood, mean (SD)1.4 (1.4)2.9 (2.9)0.001 *
Walking ability, mean (SD)1.4 (1.7)2.7 (2.9)0.006 *
Normal work, mean (SD)1.7 (2.1)3.5 (3.2)0.001 *
Relations with other people, mean (SD)1.5 (1.9)2.7 (3.0)0.016 *
Sleep, mean (SD)1.6 (1.8)3.9 (3.4)<0.001 *
Enjoyment of life, mean (SD)1.7 (1.9)3.3 (3.0)0.003 *
Reduced range of motion, n (%)3 (6.4)19 (35.8)0.001 *
Pain scar assessment scale, mean (SD)
Painfulness of scar1.3 (0.7)1.8 (1.6)0.025 *
Itching of scar1.2 (0.5)2.0 (1.6)0.001 *
Different colour scar3.7 (2.7)5.2 (3.4)0.018 *
Stiffness of scar3.1 (2.5)3.6 (3.0)0.329
Different thickness of scar3.4 (2.6)3.8 (2.7)0.408
Irregularity of scar2.7 (2.4)4.2 (3.2)0.010 *
Analgesic medications for pain, n (%)3 (6.4)14 (26.4)0.008 *
Opioid medications1 (2.1)4 (7.5)0.367
Codeine-acetaminophen0 (0.0)3 (5.7)0.245
Hydromorphone0 (0.0)1 (1.9)1.000
Non-opioid medications3 (6.4)13 (24.5)0.015 *
Acetaminophen3 (6.4)7 (13.2)0.328
NSAID0 (0.0)3 (5.7)0.245
Gabapentin0 (0.0)2 (3.8)0.497
BPI—Brief Pain Inventory; MCS—Mental Component Summary; NSAID—Non-steroidal anti-inflammatory; PCS—Physical Component Summary; SF-36—Short Form 36; SF-MPQ—Short Form; McGill Pain Questionnaire; * p < 0.05.
Table
Table 4. Univariate analysis of preoperative variables.
Table 4. Univariate analysis of preoperative variables.
CharacteristicsNo Pain (n = 47)Persistent Pain (n = 53)All Patients (n = 100)p-Value
Preoperative factors
Age, mean (SD)55.9 (11.2)53.9 (10.9)54.8 (11.0)0.364
Ethnicity, n (%) 0.489
European41 (87.2)48 (90.6)89 (89.0)
Japanese1 (2.1)1 (1.9)2 (2.0)
Persian/Arabic1 (2.1)0 (0.0)1 (1.0)
Native American2 (4.3)0 (0.0)2 (2.0)
Other2 (4.3)4 (7.5)6 (6.0)
Marital Status, n (%) 0.167
Married/Common Law36 (78.3)40 (75.5)76 (76.8)
Separated/Divorced6 (13.0)4 (7.5)10 (10.1)
Single4 (8.7)4 (7.6)8 (8.1)
Widowed0 (0.0)5 (9.4)5 (5.1)
Body mass index (kg/m2), mean (SD)28.6 (6.5)28.1 (6.8)28.4 (6.7)0.696
Education, n (%) 0.729
Less than high school1 (2.2)2 (3.8)3 (3.0)
High school14 (30.4)14 (26.4)28 (28.3)
College diploma18 (39.4)17 (32.1)35 (35.4)
University degree13 (28.3)20 (37.7)33 (33.3)
Employment Status, n (%) 0.027 *
Employed26 (56.5)41 (77.4)67 (67.7)
Unemployed20 (43.5)12 (22.6)32 (32.3)
Gross Household Yearly Income, n (%) 0.569
<$20,0004 (8.7)5 (9.4)9 (9.1)
$20,000–$44,9998 (17.4)6 (11.3)14 (14.1)
$50,000–$69,9995 (10.9)11 (20.8)16 (16.2)
$70,000–$100,00010 (21.7)10 (18.9)20 (20.2)
>$100,00019 (41.3)21 (39.6)40 (40.4)
Smoking Status, n (%) 0.964
Non-smoker32 (69.6)38 (71.7)70 (70.7)
Current smoker5 (10.9)5 (9.4)10 (10.1)
Previous smoker (≥ 1 month ago)9 (19.6)10 (18.9)19 (19.2)
Diabetes, n (%)5 (10.6)2 (3.8)7 (7.0)0.249
PCS Scores, mean (SD)9.1 (7.3)14.4 (10.2)11.9 (9.4)0.005 *
APAIS Scores, mean (SD)13.6 (4.9)16.3 (5.5)15.0 (5.4)0.013 *
APAIS—Amsterdam Preoperative Anxiety and Information Scale; PCS—Pain Catastrophizing Scale; * p < 0.05.
Table
Table 5. Univariate analysis of intraoperative variables.
Table 5. Univariate analysis of intraoperative variables.
CharacteristicsNo Pain (n = 47)Persistent Pain (n = 53)p-Value
Intraoperative factors
Surgery duration (hours), mean (SD)0.7 (0.4)0.8 (0.5)0.168
Intraoperative medications, n (%)
Propofol infusion29 (61.7)40 (75.5)0.137
Volatile anesthetic gas44 (93.6)52 (98.1)0.252
Ketamine1 (2.1)2 (3.8)1.000
Dexamethasone29 (61.7)22 (41.5)0.044 *
Local wound infiltration32 (68.1)32 (60.4)0.423
Surgical procedure, n (%) 0.072
Lumpectomy38 (80.9)38 (71.7)0.285
Mastectomy9 (19.1)15 (28.3)0.285
Axillary node resection 32 (68.1)38 (71.7)0.694
Type of axillary node resection 0.585
Axillary lymph node dissection (ALND)2 (4.3)5 (9.4)
Sentinel lymph node biopsy (SLNB)30 (63.8)33 (62.3)
Placement of implants1 (2.1)0 (0.0)0.470
Placement of expanders1 (2.1)3 (5.7)0.620
Peri-areolar incision 1 (2.1)0 (0.0)0.470
Drains placed9 (19.1)14 (26.4)0.389
* p < 0.05.
Table
Table 6. Univariate analysis of postoperative variables.
Table 6. Univariate analysis of postoperative variables.
CharacteristicsNo Pain (n = 47)Persistent Pain (n = 53)p-Value
Postoperative factors (POD 1–3)
Medication use
Opioids, n (%)26 (55.3)35 (66.0)0.309
Acetaminophen, n (%)12 (25.5)24 (45.3)0.060
NSAIDs/COX2, n (%)4 (8.5)7 (13.2)0.534
Mean pain score on movement, mean (SD)2.00 (1.83)3.41 (1.96)0.001 *
Mean pain score at rest, mean (SD)1.36 (1.52)2.15 (1.52)0.013 *
Received adjuvant chemotherapy, n (%)10 (21.3)22 (41.5)0.030 *
COX—cyclooxygenase; NSAID—Non-steroidal anti-inflammatory; POD—Postoperative days; * p < 0.05.
Table
Table 7. Adjusted analysis on pre-, intra-, and post-operative predictors.
Table 7. Adjusted analysis on pre-, intra-, and post-operative predictors.
VariableOdds Ratio95% CIp-Value
LowerUpper
Preoperative Model
Diabetes0.620.103.860.605
Age0.550.971.060.553
Employment Status2.701.049.660.042 *
PCS Scores1.050.991.110.098
APAIS Scores1.090.981.180.107
Intraoperative Model
Surgery Duration1.310.463.740.614
Mastectomy2.240.727.020.165
Propofol infusion2.230.865.780.099
Ketamine1.270.1016.050.852
Dexamethasone0.450.191.060.067
Postoperative Model
Mean pain score at movement1.631.062.510.026 *
Mean pain score at rest0.910.531.540.723
Opioid consumption0.910.322.620.865
Acetaminophen use2.671.016.990.047 *
Adjuvant chemotherapy3.301.199.150.022 *
APAIS—Amsterdam Preoperative Anxiety and Information Scale; PCS—Pain Catastrophizing Scale; * p < 0.05.
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Sahni, S.; Patel, R.; Wang, L.; Miles, S.; Dana, E.; Khan, J.S. Characteristics and Perioperative Risk Factors for Persistent Pain after Breast Cancer Surgery: A Prospective Cohort Study. Surgeries 2023, 4, 301-316. https://doi.org/10.3390/surgeries4030031

AMA Style

Sahni S, Patel R, Wang L, Miles S, Dana E, Khan JS. Characteristics and Perioperative Risk Factors for Persistent Pain after Breast Cancer Surgery: A Prospective Cohort Study. Surgeries. 2023; 4(3):301-316. https://doi.org/10.3390/surgeries4030031

Chicago/Turabian Style

Sahni, Sachin, Ronak Patel, Li Wang, Sarah Miles, Elad Dana, and James S. Khan. 2023. "Characteristics and Perioperative Risk Factors for Persistent Pain after Breast Cancer Surgery: A Prospective Cohort Study" Surgeries 4, no. 3: 301-316. https://doi.org/10.3390/surgeries4030031

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