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Cochrane Database of Systematic Reviews Protocol - Intervention

Perioperative systemic nonsteroidal anti‐inflammatory drugs (NSAIDs) in women undergoing breast surgery

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Abstract

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:

To assess the effects of perioperative NSAID use versus non‐NSAID analgesics in women undergoing any type of breast surgery.

Background

Description of the condition

A hematoma, or a collection of blood inside the axilla or breast surgical site, is one potential complication following breast surgery. A hematoma can require additional surgery to drain and/or readmission to the hospital, and it may predispose patients to infection (Cheng 2011). Addressing these complications may limit the amount of money reimbursed to providers (Smith 2017), factoring into their decision to perform a lower yield procedure with a lower risk of complications (De Souza 2012; Smith 2017). Furthermore, hematomas may increase patients' emotional stress and physical pain (Kaoutzanis 2017). While the incidence of hematomas associated with breast surgery requiring return to the operating room is relatively low (less than 2.1%) (Collins 2012; Gobble 2014; Yan 2015), the large number of breast surgery procedures performed every year makes its negative consequences significant at a population level. Nonsteroidal anti‐inflammatory drugs (NSAIDs) are being increasingly used to treat postoperative pain, and it is unclear whether there is an association between perioperative NSAID use and an increased risk of hematoma development at the surgical site.

Breast surgery encompasses oncologic, reconstructive, and cosmetic procedures. An estimated 316,120 women were diagnosed with breast cancer in 2017 in the USA, with approximately 97% of stage I and II, 93% of stage III, and 31% of stage IV patients undergoing surgical treatment (ACS 2017). Commonly performed oncologic breast procedures include lumpectomy, mastectomy, sentinel lymph node biopsy, and axillary dissection. In 2017, members of the American Society for Plastic Surgery (ASPS) performed over 600,000 reconstructive and cosmetic breast cases, including implant‐based reconstruction, autologous flap reconstruction, mastopexy, and augmentation, among others (ASPS 2017). Approximately 29% of these were reconstructive procedures, while the remaining 71% were cosmetic procedures (ASPS 2017).

Description of the intervention

The American Society of Anesthesiologists (ASA) released its most recent practice guidelines for acute pain management in the perioperative period in 2016 (Chou 2016). Medication selection for perioperative pain management is guided by patient factors, but an underlying principle is a multimodal approach, that is, where two or more drugs with differing modes of action are used to treat acute surgical pain.

Opioid drugs remain a mainstay of analgesia; however, 20 years ago Kehlet 1997 introduced the now‐common recommendation of an "around‐the‐clock" regimen of a nonsteroidal anti‐inflammatory drug (NSAID, for example ketorolac, flurbiprofen, diclofenac, celecoxib) and/or acetaminophen (paracetamol), unless contraindicated. This concept has been more recently adapted into standardized breast surgical treatment plans (Batdorf 2015; Bonde 2015; Bonde 2016; Davidge 2013). NSAID use has demonstrated equivalent efficacy to opioids and similar postoperative bleeding when compared to controls in a wide range of surgical procedures (Gobble 2014). Perioperative NSAID use for patients undergoing endoscopic sinus surgery reduced postoperative rescue analgesics that included opioid use in many studies, with bleeding seen in 0.8% of patients (Svider 2018). Perioperative NSAID use in pediatric patients undergoing tonsillectomy concluded there was insufficient evidence to exclude an increased risk of bleeding (Lewis 2013).

How the intervention might work

NSAIDs inhibit cyclooxygenase (COX) enzymes, thereby reducing prostaglandin synthesis and an inflammatory response that causes pain. There are two types of COX enzymes: COX‐1 and COX‐2. Both types produce prostaglandins that promote inflammation, pain, and fever. Most NSAIDs are reversible inhibitors; however, aspirin binds permanently to COX enzymes, leading to a prolonged duration of effect.

The use of NSAIDs perioperatively may be associated with bleeding complications. This is because NSAID inhibition of COX‐1 reduces thromboxane A2, which mediates platelet aggregation. Most cells, including those in the stomach, express COX‐1, which provides a protective effect in gastric tissue, so NSAIDs' inhibition of COX‐1 enzymes can lead to bleeding from the stomach.

Non‐selective NSAIDs also inhibit COX‐2, and their effects can be different to those that inhibit COX‐1 enzymes. COX‐2 is the most important contributor to inflammation, hypertension, and possibly cancer. It is induced by immune cell factors, shear stress, and tumor promoters. Selective COX‐2 inhibitors target the inflammatory process while minimizing gastric and non‐gastric bleeding. They may reduce the risks of hematoma and other significant bleeding after breast surgery, while still providing adequate pain control in comparison to non‐selective COX‐1/COX‐2 inhibitors by reducing endothelial prostacyclin and consequently increasing platelet aggregation. In this regard, focusing on the NSAID ketorolac may be misleading, as this has the highest COX‐1 selectivity of all the NSAIDs (Cheng 2016; Jarupongprapa 2013; Schmidt 2016).

A retrospective analysis of perioperative ketorolac use in patients undergoing breast reduction surgery demonstrated a three‐fold increase in the likelihood of developing a hematoma and the need to return to the operating room for hematoma removal (Cawthorn 2012). A randomized controlled trial (RCT) comparing an NSAID (ketorolac) to a non‐NSAID (metamizol) for postoperative pain in elective plastic surgery reported postoperative bleeding in two patients receiving an NSAID that required a return to the operating room (Marin‐Bertolin 1997). Other studies have demonstrated no difference in bleeding rates between different NSAIDs (i.e. flurbiprofen or ketorolac) and placebo (Gobble 2014; Sun 2013). In patients receiving perioperative diclofenac, the risk of postoperative bleeding was higher than placebo; however, none of the patients needed reoperation for bleeding or hematoma (Cheng 2016).

A large number of studies have investigated whether NSAIDs are efficacious in reducing postoperative pain. Meta‐analyses of RCTs comparing opioid medication alone versus opioids plus NSAIDs in surgical patients found that the addition of ketorolac to intravenous morphine significantly improved pain scores and reduced analgesic use compared to intravenous morphine alone; however, these benefits were not as clear when intravenous patient‐controlled opioid analgesia was compared alone to a selective COX‐2 inhibitor or a nonselective NSAID (ASA 2012). Another meta‐analysis of RCTs found the addition of an NSAID to be superior to placebo in reducing postoperative pain (Gobble 2014). When selective COX‐2 inhibitors (rofecoxib, etoricoxib, celecoxib, and parecoxib) were administered preoperatively, they significantly reduced postoperative pain when compared to placebo (Nir 2016). However, COX‐2 inhibitors have been associated with early failure of vascular free flaps (i.e. tissue that is disconnected from its original blood supply and reconnected at another location in the body) due to thrombosis from a lack of thromboxane A2 inhibition and platelet aggregation (Al‐Sukhun 2006; Bonde 2017).

Recent evidence has demonstrated that perioperative NSAIDs (flurbiprofen axetil and ketorolac) may decrease the recurrence of breast cancer by inhibiting pro‐inflammatory and pro‐tumorigenic factors in patients undergoing surgery. These inflammatory factors impair the immune system and promote tumor recurrence and metastasis (Desmedt 2018; Forget 2013; Wen 2015). Other non‐NSAID pain medications lack these anti‐inflammatory characteristics. Even within the different classes of NSAIDs, results vary within patient demographics. A comparison of intraoperative ketorolac versus diclofenac in patients with an increased body mass index showed that ketorolac but not diclofenac reduced the incidence of distant metastasis (Desmedt 2018).

Why it is important to do this review

With the recent focus on the over‐prescribing of opioids in the literature, it is important to assess the effectiveness and safety of non‐opioid pain medication regimens including NSAIDs (HHS 2016). Clinicians have differing opinions on the safety of perioperative NSAIDs for breast surgery given the unclear risk/benefit ratio. A hematoma during a plastic surgery procedure can result in complete loss of the reconstruction (Mikhaylov 2018).

Previous systematic reviews, focused on evaluating NSAID analgesics in breast surgery, were limited in scope (Cheng 2016; Gobble 2014; Stephens 2015). Stephens 2015 conducted a systematic review to assess the association between perioperative use of ketorolac and the incidence of hematomas in 981 patients undergoing face and breast plastic surgery procedures. Although they found a two‐fold increase in the incidence of hematomas in patients who received ketorolac, this difference was not statistically significant (Stephens 2015). A single‐institution study by Sharma 2001 also did not find any significant association between the use of ketorolac and the incidence of hematomas in breast reconstruction procedures. The relatively small sample sizes included in these studies may potentially account for the lack of association demonstrated between perioperative NSAID use and hematoma development. Additionally, these results addressed very specific patient populations, so the conclusions may not be generalizable to patients undergoing alternate breast surgery procedures. Furthermore, some countries rarely use ketorolac as the perioperative NSAID. An evaluation of other NSAIDs more commonly used around the world needs to be completed.

As perioperative NSAID use has demonstrated a clinical decrease of recurrence of breast cancer, it needs to be determined if this clinical effect would outweigh contraindications to receiving NSAIDs in these patients. The American Society of Plastic Surgeons (ASPS) recommends that patients stop taking NSAIDs, including aspirin, prior to breast surgery (ASPS 2018). Research has not yet clarified the risks and benefits of all NSAIDs between cosmetic and reconstructive breast surgery patients. Assessing different proportions of COX‐1/COX‐2 inhibition and patient outcomes may provide a more uniform standard of care. There is currently no Cochrane Review on perioperative NSAID use for breast surgery. These results will help lead to more conclusive surgical practice guidelines for plastic surgeons encountering perioperative outcomes.

The impact of NSAID use is a very complex topic. Although the focus of this Cochrane Review is primarily on surgical site bleeding outcomes, there are a multitude of important perioperative outcomes, including venous thromboembolism, major adverse cardiac events, acute kidney injury, gastrointestinal ulceration, and potential cancer recurrence or remission. These outcomes increase with age (Wongrakpanich 2018). In addition, other comorbidities can increase the frequency of these outcomes (Harirforoosh 2013; Wongrakpanich 2018). COX‐1 and COX‐2 inhibitor selectivity is highly relevant when assessing the risk‐benefit balance in this regard.

Objectives

To assess the effects of perioperative NSAID use versus non‐NSAID analgesics in women undergoing any type of breast surgery.

Methods

Criteria for considering studies for this review

Types of studies

We will include all randomized controlled trials (RCTs) looking at perioperative NSAID use in women undergoing breast surgery, prioritizing and presenting them separately in the review. In the absence of randomized trials, we will include well‐designed cohort or case‐control studies.

Types of participants

We will include women over the age of 18 and undergoing any type of breast surgery. This includes: oncologic, reconstructive, or cosmetic surgery. Trials will include participants receiving a specified perioperative NSAID. However, we will exclude trials that do not report results of our desired population separately.

Types of interventions

All interventions that compare perioperative systemic NSAID use. The comparisons can include:

  • NSAID versus placebo;

  • NSAID versus no intervention;

  • NSAID versus other analgesic drug.

Terms used to refer to NSAIDs can include aspirin, salicylic acid, diflunisal, paracetamol, acetaminophen, dipyrone, propyphenazone, indomethacin, diclofenac, aceclofenac, etodolac, ketorolac, sulindac, ibuprofen, naproxen, fenoprofen, flurbiprofen, ketoprofen, mefenamic acid, meclofenamate, meloxicam, piroxicam, nabumetone, celecoxib, etoricoxib, parecoxib, and rofecoxib.

This will include any non‐selective COX or selective COX‐2 inhibitors administered by any route (intravenous, intramuscular, rectal, or oral) during hospital admission.

Types of outcome measures

Primary outcomes

  • Incidence of breast hematoma within 90 days of breast surgery (requiring reoperation, interventional drainage, or no treatment). Hematomas will be measured with clinical diagnosis alone or imaging.

  • Postoperative pain intensity within 24 (±12) hours of surgery. Postoperative pain will be measured with validated pain scales including the numerical rating scale (NRS), visual analogue scale (VAS), and verbal categorical rating scale (VRS), which are ascertained from reviews on pain assessment (Hjermstad 2011; Younger 2009).

Secondary outcomes

  • Incidence rate or severity of postoperative nausea, vomiting, or both

  • Bleeding from any location within 90 days

  • Need for blood transfusion

  • Other side effects of NSAID use

  • Opioid use within 24 (±12) hours of surgery

  • Length of hospital stay

  • Breast cancer recurrence

  • Non‐prescribed NSAID use

Severity of postoperative nausea and vomiting may be reported with the following scales: Likert scales, VAS, postoperative nausea and vomiting (PONV) intensity scale (Wengritzky 2010), or PONV impact scale (Myles 2012).

We will determine opioid use in studies that permitted co‐administration of opioids, evaluating mean opioid use (in mg) over various study time intervals and standardizing into morphine equivalents using opioid conversion tables (Jacox 1994).

Other secondary outcomes will be based on the measures used by the included studies.

Search methods for identification of studies

Electronic searches

We will search the following databases.

Searching other resources

We will try to identify further studies by handsearching reference lists of identified relevant trials or reviews and obtaining a copy of the full article for each reference reporting a potentially eligible trial. Where this is not possible, we will attempt to contact authors to provide additional information.

Data collection and analysis

Selection of studies

Two authors (KMK, MRM) will independently screen all study titles and abstracts from the results of our search strategy. In case of disagreement on study inclusion, these two authors will meet to discuss eligibility, involving a third author (RP) if necessary. We will follow a similar process during full‐text screening. The selection process will be recorded in the PRISMA flow diagram and at every step, and we will record the reasons for exclusion in the 'Characteristics of excluded studies' table. There will be no language restrictions; if necessary, we will have non‐English papers translated. References will be managed with Covidence.

Data extraction and management

Two authors (KMK, MRM) will independently extract quantitative data relating to the primary and secondary outcomes using standardized data extraction forms and Covidence systematic review software (Covidence). Information extracted from each included trial will consist of the following.

  • Characteristics of trial participants (age, type of breast surgery, breast cancer history).

  • Type of intervention (type, dose, duration, and frequency of NSAID and/or non‐NSAID, placebo, or no treatment).

  • Type of outcome measure (occurrence and treatment of breast hematoma, level of pain, occurrence or severity of PONV, length of stay).

  • Study information data (e.g. study design, sample size of each study group, year, location, author list), recorded for the purposes of identification and quality appraisal.

  • Risk of bias domains (Higgins 2011).

  • Methods used to control for confounders (for non‐randomized studies).

  • Adjusted and unadjusted outcome measures (for non‐randomized studies).

  • List of variables authors have included in analyses for adjusted estimates (for non‐randomized studies).

These study authors will meet to determine whether any disagreements exist in the data extracted and resolve disagreements through discussion, involving a third author (RP) when necessary. We will identify reports pertaining to the same study, selecting a single one as the primary reference for inclusion based on completeness of reporting.

Assessment of risk of bias in included studies

Two authors (KMK, MRM) will independently assess risk of bias using Cochrane's 'Risk of bias' assessment tool (Higgins 2011), resolving any disagreement through discussion and involving a third author (GDR) when necessary. We will evaluate the following items in a 'Risk of bias' table.

Randomized studies

  • Random sequence generation (to assess possible selection bias).

  • Allocation concealment (to assess possible selection bias).

  • Blinding of participants and personnel (to assess possible performance bias).

  • Blinding of outcome assessment (to assess possible detection bias).

  • Incomplete outcome data (to assess possible attrition bias).

  • Selective outcome reporting (to assess possible reporting bias).

  • Other bias.

Moreover, we will assess all studies to evaluate if they are at overall high risk of bias according to Higgins 2011, considering how the magnitude of bias with random sequence generation, allocation concealment, incomplete outcome data, and selective reporting will impact the findings. We will consider studies to be at low overall risk of bias if they use a truly random process for sequence generation, conceal allocation, have no missing outcomes data, do not selectively report pre‐specified outcomes. Otherwise, we will classify the studies as being at high risk of overall bias and assess the impact of this risk using sensitivity analysis.

Non‐randomized studies

We will use the Risk of Bias in Non‐randomized Studies of Interventions (ROBINS‐I) tool to assess bias in non‐randomized studies (Sterne 2016). This will include evaluation of the following items.

  • Baseline patient characteristics (to assess possible bias in selection of participants into the study).

  • Adjustments for confounding variables (to assess possible bias due to confounding).

  • Classification of interventions.

  • Deviations from intended interventions.

  • Missing data.

  • Selection of reported results.

We will document reasons for each classification, resolving disagreements through discussion between the two authors (KMK, MRM) and involving a third review author (RP) if necessary. We use the ROBINS‐I Stage 1 tool at protocol stage to pre‐specify the review question, confounding domains, and co‐interventions.

Review question

  • Does perioperative administration of an NSAID control postoperative pain without increasing the risk of hematoma within the first 90 days of the operation?

Confounding factors

We consider the following factors to be relevant to all or most studies.

  • Primary diagnosis.

  • Age (age > 75 years associated with increased risk of bleeding).

  • Previous severe bleeding on NSAIDS (WHO grade 3 or 4).

  • Prior major cardiac event (serious cardiovascular thrombotic events, myocardial infarction, and stroke).

  • Use of anticoagulation during the study.

  • Performance status (Eastern Cooperative Oncology Group (ECOG)).

  • Presence of bleeding disorder.

  • Stage 4 or 5 chronic kidney disease.

  • Dialysis.

Co‐interventions

These potential co‐interventions could be different between treatment groups and have an impact on outcomes.

  • Use of over‐the‐counter NSAIDs.

  • Use of anticoagulation.

  • Use of antiplatelet medication.

  • Over‐the‐counter or herbal medicines.

Measures of treatment effect

For dichotomous outcomes (i.e. incidence of hematoma requiring reoperation within 90 days of breast surgery; incidence of hematoma requiring drainage within 90 days of breast surgery; and incidence of hematoma, regardless of treatment, within 90 days of breast surgery), we will measure the effect using risk ratio and 95% confidence intervals.

For continuous outcomes collected with different scales (i.e. postoperative pain at 24 (±12) hours from surgery, postoperative nausea and vomiting at 24 (±12) hours from surgery), we will measure the effect using standardized mean differences with 95% confidence intervals.

For continuous outcomes collected on the same scale (i.e. length of stay and opioid use), we will measure the effect using mean differences with corresponding standard deviation and 95% confidence intervals.

Unit of analysis issues

We do not expect to find relevant cluster‐randomized studies. We will appropriately consider the unit of analysis to be each individual patient.

Dealing with missing data

If data are missing, we will attempt to obtain them from study authors and perform an intention‐to‐treat (ITT) analyses if possible. Otherwise, we will perform available‐case analyses. We will investigate attrition rates (e.g. dropouts, losses to follow‐up and withdrawals) and critically appraise issues of missing data. We will not impute missing data.

Assessment of heterogeneity

We will initially assess clinical and methodological heterogeneity of included trials qualitatively with regard to patient characteristics, type of breast surgery, NSAIDs used, and measurement of outcomes. We will extract, record, and qualitatively evaluate possible sources of heterogeneity from the data.

We will assess statistical heterogeneity by calculating I2 (Higgins 2011), considering statistical heterogeneity as substantial if I2 is greater than 50% and the T2 is greater than zero or there is a low P value (less than 0.1) in the Chi2 test for heterogeneity (Higgins 2011).

Assessment of reporting biases

If we have 10 or more studies in our meta‐analysis of the primary outcome, we will assess reporting bias by generating funnel plots (Higgins 2011).

Data synthesis

Statistical analysis will be conducted using Review Manager 5 software (RevMan 2014). We will use a fixed‐effect model for the meta‐analysis if it is acceptable to assume the trials are estimating the same treatment effect. If we detect clinical heterogeneity between the trials, we will use a random‐effects model to produce an overall summary of the average clinical treatment effect. If we detect substantial statistical heterogeneity, we will not pool results from the meta‐analysis but instead report the data as a narrative.

We will pool dichotomous outcomes using Mantel‐Haenszel analysis for fixed‐effect model or DerSimonian and Laird for a random‐effects model, and we will pool continuous outcomes using the inverse‐variance method.

Subgroup analysis and investigation of heterogeneity

We plan to analyze the following subgroups, if information and adequate number of studies and population sample are available.

  • Type of breast surgery.

  • Type of NSAID (nonselective, COX‐2 inhibitor, aspirin).

  • Different drug doses and route of administration.

  • Breast cancer status of included women (history of breast cancer, no history of breast cancer).

We will calculate heterogeneity among the different subgroups and evaluate heterogeneity by using I2 and the aforementioned threshold.

Sensitivity analysis

If information and an adequate number of studies and population samples are available, we plan to perform a sensitivity analysis by excluding studies with unclear or high risk of bias for all risk of bias domains.

Following each sensitivity analysis, we will evaluate heterogeneity and outcomes, including risk ratio and 95% CIs, comparing results to those from the primary meta‐analyses.

'Summary of findings' table

Two authors (KMK, MRM) will assess the certainty of evidence according to the GRADE approach for seven outcomes of interest, as described in the Cochrane Handbook for Systematic Reviews of Interventions (Schünemann 2011). We will prepare a 'Summary of findings' table using GRADE software (GRADEproGDT), presenting findings for the following seven outcomes: breast hematoma; breast hematoma requiring reoperation or interventional drainage; breast hematoma not requiring treatment; postoperative pain; postoperative nausea, vomiting, or both; bleeding from any location; and length of hospital stay.