Objectives
This is a protocol for a Cochrane Review (intervention). The objectives are as follows:
To assess the benefits and harms of scalp cooling for the prevention of hair loss from adjuvant or neoadjuvant chemotherapy in women with early breast cancer.
Background
The synthesis PICO for this review is as follows.
Population: women receiving adjuvant or neoadjuvant chemotherapy for early breast cancer
Intervention: scalp cooling
Comparator: no treatment to prevent hair loss
Outcome: hair loss induced by chemotherapy
Description of the condition
Chemotherapy drugs used in the treatment of breast cancer invariably cause hair loss, known as chemotherapy‐induced alopecia, as a side effect. When combined with endocrine therapy, chemotherapy has helped increase the survival rate for individuals with early‐stage breast cancer to nearly 94% [1]. However, for many cancer survivors, hair loss due to chemotherapy can significantly impact body image, both physically and emotionally [2, 3, 4]. Chemotherapy‐induced alopecia typically appears two to four weeks after the start of chemotherapy and can last until six to nine months after its conclusion. Unfortunately, some women may not experience satisfactory hair regrowth [5, 6, 7].
The likelihood of experiencing chemotherapy‐induced alopecia varies depending on the chemotherapy drugs used: it can occur in 80% or more of people treated with antimicrotubule agents (e.g. paclitaxel), in 60% to 100% of those receiving topoisomerase inhibitors (e.g. doxorubicin) and in 60% or more of those treated with alkylating agents (e.g. cyclophosphamide) [8].
This review will focus on women with early breast cancer who receive chemotherapy as part of neoadjuvant therapy.
Description of the intervention and how it might work
Scalp cooling methods have been used in outpatient settings since the late 1970s to prevent chemotherapy‐induced alopecia. Initially, this involved applying a cooled object to the head, which would gradually warm and require frequent replacement [9]. Over time, more advanced systems were developed where cooled refrigerant was circulated through the headgear, allowing computerised control of a constant temperature over extended periods.
The Dutch Scalp Cooling Registry, an open patient registry, has collected data on scalp cooling since 2006 [10, 11], with the majority being people with breast cancer undergoing adjuvant or neoadjuvant chemotherapy. High success rates have been reported, particularly in people receiving treatment with taxanes, with hair preservation rates reaching up to 80% to 90%. By comparison, in clinical practice, the standard of care group typically does not receive a specific preventive measure for alopecia. Adverse effects associated with scalp cooling are generally mild and may include discomfort, headaches, cold sensation, dizziness, and occasionally, local skin reactions.
Despite these advancements, the integration of scalp cooling into routine clinical practice remains limited and continues to evolve. Since 2015, scalp hypothermia has been explored as a strategy to manage chemotherapy‐induced alopecia, elucidating this previously inevitable issue [9, 12, 13].
The concept behind scalp hypothermia is to reduce blood flow to the scalp, thereby limiting the exposure of hair follicles to cytotoxic drugs [14]. However, there have been concerns that reducing blood flow to the skin might impair drug delivery and potentially increase the risk of cancer spreading to the skin. Several studies have reported that scalp cooling does not increase the risk of scalp metastases or worsen prognosis [15, 16, 17, 18]. It is advisable that the most recent evidence, particularly studies with long‐term follow‐up, be considered when evaluating the safety and efficacy of scalp cooling.
Why it is important to do this review
Previous systematic reviews of scalp cooling for the prevention of chemotherapy‐induced alopecia, primarily involving women with breast cancer, have demonstrated the efficacy of these interventions [17, 19, 20]. However, these non‐Cochrane reviews and meta‐analyses included data only up to 2022 [17, 19, 20], and may be subject to language bias [20, 21]. Further, scalp cooling remains a relatively new technique that poses challenges for implementation in the clinic and still requires further improvement.
Since the publication of the earlier reviews, new randomised controlled trials (RCTs) have been published, making this an opportune time to update and strengthen evidence from RCTs in a comprehensive Cochrane review. This review will be distinct in that it will focus exclusively on RCTs involving women with early breast cancer receiving chemotherapy either before or after surgery. It will also incorporate the most up‐to‐date data, a detailed analysis of quality of life outcomes, the specific scalp‐cooling methods used and an evaluation of the associated financial implications – areas not fully addressed in previous reviews.
For women with breast cancer, preserving a cosmetic appearance is important both psychologically and physically. Chemotherapy‐induced alopecia can influence a woman's decision to undergo chemotherapy, even when it may improve prognosis. Therefore, it is essential that both patients and healthcare providers are informed about available interventions to prevent alopecia and the supporting evidence base.
The Clinical Practice Guideline for Appearance Care of Cancer Survivors was developed to address these concerns. Findings from this Cochrane review can contribute meaningfully and enhance these guidelines. Currently, the Japanese Association of Supportive Care in Cancer (JASCC) guideline outlines a "weak recommendation" for scalp cooling, limited to people with breast cancer undergoing perioperative chemotherapy, based on "moderate" strength evidence [22]. The guideline notes the need for further research on quality of life, long‐term efficacy and safety outcomes. The National Comprehensive Cancer Network (NCCN, USA) guideline provides a grade 2A recommendation for scalp cooling, including for recurrent breast cancer, indicating lower‐level evidence but expert consensus [23]. Similarly, the European Society of Medical Oncology (ESMO) guideline gives a grade B recommendation, suggesting general support for its use [24].
However, these guidelines are based on somewhat dated evidence, often not limited to RCTs. This review aims to provide up‐to‐date, high‐quality evidence to support future clinical guideline updates about the role of scalp cooling in preventing chemotherapy‐induced alopecia in women with breast cancer.
Objectives
To assess the benefits and harms of scalp cooling for the prevention of hair loss from adjuvant or neoadjuvant chemotherapy in women with early breast cancer.
Methods
We will follow the Methodological Expectations of Cochrane Intervention Reviews (MECIR) when conducting the review [25], and adhere to PRISMA when reporting [26].
Criteria for considering studies for this review
Types of studies
We will include individual randomised controlled trials (RCTs) comparing scalp‐cooling devices and no treatment to prevent hair loss in people undergoing adjuvant or neoadjuvant chemotherapy for early breast cancer.
Quasi‐RCTs (i.e. studies where random allocation is attempted, but the method is not considered truly random (e.g. randomised by day of week)) will not be eligible. We will also exclude cross‐over or cluster‐randomised trials, review articles, cross‐sectional studies and case reports.
We will not apply any filters for language or year of publication.
Types of participants
We will include women aged 18 years or older undergoing adjuvant or neoadjuvant chemotherapy for early breast cancer, but exclude women with recurrence or metastases.
We will include studies of several cancer types only if results of women with breast cancer are provided separately in stratified analyses.
Types of interventions
We will include RCTs comparing scalp‐cooling devices versus no treatment to prevent hair loss in women with early breast cancer undergoing adjuvant or neoadjuvant chemotherapy. If scalp cooling is used in conjunction with other interventions, such as applying something to the scalp, we will exclude these studies from this review because the purpose of this review is to evaluate the effect of scalp cooling.
We will include any type of scalp‐cooling devices, such as those using refrigerant‐like substances to cool the scalp, causing variations in scalp temperature, as well as devices that use a computer‐controlled system to maintain a constant temperature by continuously circulating a cooled liquid. Additionally, if possible, we will consider devices with or without priming, and take into account the cooling time implemented.
Outcome measures
We will include trials for which the study design, participants, interventions and comparators fulfil the inclusion criteria, irrespective of whether our prespecified outcomes are reported.
Critical outcomes
Hair loss induced by chemotherapy.
We will compare the extent of hair loss before and after chemotherapy, according to the criteria used in each trial.
There may be multiple assessment criteria for the degree of hair loss. Therefore, we will rank the assessment criteria as follows. The highest priority will be given to internationally recognised and validated assessment methods, such as the Common Terminology Criteria for Adverse Events (CTCAE) scale and the World Health Organization (WHO) hair loss scale [27]. This will be followed by assessment criteria that have been validated and are in use in some parts of the world, such as the Dean scale for hair loss [28]. In addition, evaluation methods that have only been defined in one study and have not been validated will be excluded from consideration for review. As for the CTCAE scale, we will consider Grade 0 (no hair loss) or Grade 1 (less than 50% hair loss, not requiring a wig) to have hair preservation and Grade 2 (greater than 50% hair loss, requiring the use of a wig) as failure. In terms of the timing of outcome assessment, this will take place before the administration of chemotherapy, between regimens if two are administered, and within one month after the final chemotherapy dose.
Serious adverse events related to scalp cooling, such as headache and skin changes such that scalp cooling cannot be continued during the study period, as well as items defined in each study.
Important outcomes
Adherence to scalp cooling method, as scheduled.
Adverse events related to scalp cooling, such as feeling cold, having a headache or heaviness reported during the study.
Scalp metastasis for individuals who underwent scalp cooling, assessed at the end of the chemotherapy. If long‐term follow‐up data exist, we will also report the incidence of scalp metastasis in five‐year intervals.
Quality of life, participant satisfaction and psychological well‐being. These will be assessed by either quality of life, impact on body image, or impact on relationships and sexuality using any validated scale reported by study authors. Examples include the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ)‐C30, EORTC QLQ‐BR23, Functional Assessment of Cancer Therapy‐Breast (FACT‐B), Chemotherapy‐induced Alopecia Distress Scale (CADS) questionnaire, Body Image Scale (BIS), Measure of Body Apperception (MBA) and Hospital Anxiety and Depression Scale (HADS), if the trials report data for these outcomes. Although there are many rating scales available, it is not clear which is the most appropriate rating scale for assessing psychosocial well‐being and satisfaction related to chemotherapy‐induced alopecia. Whichever rating scale is used, it needs to be validated in the respective cultural context. However, we do expect that CADS will be prioritised, but for the reasons given above, we will prioritise the most frequently used measure from the clinical trials. As for the time point of outcome assessment, we plan to assess these at baseline and at the end of each regimen.
Financial burden, which will refer primarily to direct costs borne by individuals (out‐of‐pocket expenses).
Search methods for identification of studies
Electronic searches
We will search the following databases.
Cochrane Breast Cancer Group Specialised Register. Details of the search strategies used by the Group for the identification of studies and the procedure used to code references are outlined in the Group's module (https://breastcancer.cochrane.org/specialised-register). The Specialised Register contains coded references published up to 6 October 2022.
Cochrane Central Register of Controlled Trials (the Cochrane Library, from inception to present)
MEDLINE (Ovid, 1946 to present, see Supplementary material 1)
Embase (Ovid, 1947 to present)
WHO International Clinical Trials Registry Platform (ICTRP) search portal for all prospectively registered and ongoing trials (https://apps.who.int/trialsearch/)
US National Institutes of Health Ongoing Trials Register ClinicalTrials.gov (https://clinicaltrials.gov/)
We will not use any date or language restrictions in the electronic searches for trials.
Searching other resources
We will search through the reference lists of all included studies and any relevant systematic reviews. In addition, we will contact relevant institutions or industries, or both, to identify potentially eligible studies.
We will check information for all included studies and studies awaiting classification for any postpublication amendments, such as errata, comments, corrigenda and retractions, from CENTRAL, other medical databases and the Retraction Watch Database (https://retractiondatabase.org).
Data collection and analysis
Selection of studies
Two review authors (YK, KT) will independently screen titles and abstracts using the systematic review management software Covidence [29]. We will classify each study as 'Yes' (relevant), 'Maybe' (possibly relevant), or 'No' (irrelevant). After retrieving full‐text copies of all relevant and possibly relevant studies, two review authors (YK, KT) will independently determine if they meet the inclusion criteria. If necessary, we will contact the study authors for clarification. In the event of a disagreement regarding eligibility, we will consult a third review author (NY) to resolve the conflict.
We will record the process of study selection in sufficient detail to complete a PRISMA flow diagram [26], documenting the total number of identified, excluded, and included studies.
Data extraction and management
Two review authors (YK, KT) will independently extract data using a data extraction template form in Covidence [29].
The review team will pilot‐test the data extraction form using a sample of one to five studies to ensure clarity, consistency and comprehensiveness before full data extraction begins. We will make any necessary revisions based on feedback from the pilot phase, and document all changes. We will primarily extract data from published papers, but also actively consult supplementary sources such as study protocols, clinical trial registration information (e.g. from ClinicalTrials.gov), supplementing information by contacting study authors as necessary. We will collect the following data related to the characteristics of the included studies.
Study details, including author names, affiliations of authors, publication year and country where the study was conducted.
Methodological characteristics, including study design, whether single‐centre or multicentre, allocation method, masking (blinding) procedures, details of postrandomisation exclusions, study duration and follow‐up period.
Participant characteristics, including country where participants were enrolled, participant eligibility criteria (inclusion and exclusion criteria), participant demographic data (e.g. age, race, other relevant characteristics) and the number of participants randomised to each group.
Intervention details, including type of cooling device, duration of cooling, timing of cooling and details of the comparator.
Outcomes, including change from baseline in the degree of hair loss, proportion of participants who had scalp metastases, change from baseline in quality of life score at the end of chemotherapy, proportion of participants who experienced adverse events related to scalp cooling and how they were measured (list of assessed outcomes, definition of each outcome, outcome assessor, blinding of the assessor).
Results, including the number of participants assigned to each group, the number of participants analysed, and the number of withdrawals and reasons for withdrawal.
Funding sources and potential conflicts of interest reported by the study authors.
Corresponding author's details and contact information.
Furthermore, we will extract relevant data to assess the risk of bias for each included study. If information necessary for synthesising the results is missing, or if points are unclear from publicly available information alone, we will attempt to contact study authors at the end of the data extraction process. Any discrepancies in the extracted data will be resolved through discussion among the review authors, and if not resolved, through consultation with a third review author. One review author will export all data to Cochrane's Review Manager software [30], and a second review author will verify the data entry.
In the case of duplicate publications or multiple reports on the same primary study, we will link these publications to individual studies. We will use the most comprehensive dataset derived from all available publications and sources, with a preference for those reporting the longest follow‐up duration related to our critical or important outcomes.
Risk of bias assessment in included studies
Two review authors (YK, KT) will independently assess the risk of bias using the RoB 2 assessment tool [31], as outlined in Chapter 8 of the Cochrane Handbook for Systematic Reviews of Interventions [32]. This tool consists of an overall risk of bias and five domains: assessment of bias arising from the randomisation process, bias introduced by deviations from the intended interventions, bias arising from missing outcome data, bias in measurement of the outcome, and bias in selection of the reported result. We will use the RoB 2 Excel tool to implement RoB 2 (available from https://riskofbiasinfo.org) following the guidelines provided in Chapter 7 of the Cochrane Handbookfor Systematic Reviews of Interventions [33].
We are interested in the effect of assignment to intervention and will judge each domain as 'low risk of bias', 'some concerns', or 'high risk of bias', presenting an overall risk of bias judgement by following the algorithms in the RoB 2 tool. We will assess the overall risk of bias as 'low' if there is a low risk of bias for all domains, as 'high' if there is a judgement of a high risk of bias within any domain, and as having 'some concerns' if there is a judgement of 'some concerns' within any domain.
We will apply the RoB 2 tool to all outcomes, especially at the end of the chemotherapy, and present as supplemental data the information for each RoB judgement (including quotation, summary of information from a trial report or correspondence with the study author, as well as the consensus result for each signalling question).
If adequate information is not available from the included trials, we will contact the trial authors as appropriate to clarify the trial information or results. If we are unable to contact the trial authors, or do not receive a response within a reasonable time period, we will assess the risk of bias based on the available information. If the two review authors are unable to reach a consensus, a third review author will be consulted for a final decision. We will assess the risk of bias for the following outcomes.
Hair loss induced by chemotherapy
Serious adverse events related to scalp cooling
Adherence to scalp cooling method
Adverse events related to scalp cooling
Scalp metastasis incidence
Quality of life
Financial burden
Measures of treatment effect
We will calculate risk ratios (RR) with 95% confidence intervals (CI) for the comparison of dichotomous outcomes, including the proportion of participants with less than 50% hair loss who do not require a wig.
We will analyse continuous data as mean difference (MD) or median (range) if the same scale is used to measure an outcome, or standardised mean difference (SMD) if different scales are used to measure the same conceptual outcome, and 95% CIs. We will enter data presented on a scale with a consistent direction of effect across studies.
When different scales are used, and we calculate the SMD with a corresponding 95% CI, we will back‐translate the SMD to a scale used in the included studies, by multiplying the SMD by a typical among‐person standard deviation [34].
If possible, we will compare the pooled estimates with the minimally important difference (MID) values for continuous outcomes to aid interpretation. We will use published MIDs when available. When multiple MID estimates are available for an outcome, we will use the smallest validated MID.
Unit of analysis issues
Participants are the unit of analysis in this review. We will review whether participants have been included in more than one study by focusing on the recruitment process of participants and aim not to include individual participants twice to avoid double‐counting.
We will follow the guidance outlined in Chapter 23 of the Cochrane Handbook for Systematic Reviews of Interventions if a study includes multiple arms [35]. If a study includes multiple relevant intervention arms (e.g. different types or durations of scalp cooling), and a single control arm (no treatment to prevent hair loss), we will analyse each relevant intervention group separately against the shared control group. For example, if a study compares two different scalp cooling devices (A and B) to a 'no cooling' control, we will create two comparisons: 'scalp cooling A versus no treatment' and 'scalp cooling B versus no treatment'. To avoid double‐counting, we will use the control group data only once per outcome in a meta‐analysis, in line with Cochrane guidance [35].
If a multi‐arm study compares different scalp cooling interventions without a 'no treatment' control arm, we will not include these comparisons in our primary meta‐analysis but may discuss them narratively if deemed relevant to the overall understanding of scalp cooling effectiveness.
Dealing with missing data
In instances where data are missing or unclear, we will contact the trial investigator for clarification. If we do not receive a response within two weeks, we will conduct a complete‐case analysis under the assumption of missing‐at‐random data [36]. This assumption will be assessed by gathering information, if available, on the number of participants excluded or lost during follow‐up after randomisation, as well as the reasons behind such exclusions.
The risk of bias due to incomplete outcome data is addressed by the Cochrane RoB 2 tool. We will consider imputation methods accompanied by sensitivity analyses.
Reporting bias assessment
We will aim to evaluate selective outcome reporting by utilising the associated signalling questions of the RoB 2 tool [37]. In the case of 10 or more eligible trials, we will utilise funnel plots to help assess the presence of small‐study effects and investigate any factors that may lead to asymmetry in the plots, such as publication bias, following the guidelines provided in Chapter 13 of the Cochrane Handbook for Systematic Reviews of Interventions [38].
Synthesis methods
We will focus on the following comparison in our review synthesis: scalp cooling versus no treatment to prevent hair loss. This is the primary comparison for assessing the benefits and harms of scalp cooling for the prevention of chemotherapy‐induced alopecia in women with early breast cancer, at the end of the chemotherapy (e.g. from the date of the last chemotherapy infusion up to one month after the infusion).
We will perform a meta‐analysis using the random‐effects model since we expect there will be clinical diversity. To estimate between‐trial variance, we will use the Restricted Maximum Likelihood (REML) estimator. We will use the Hartung‐Knapp‐Sidik‐Jonkman method to calculate a CI for the meta‐analysis effect estimate when there are at least three studies and the estimate of heterogeneity is greater than zero. In other scenarios (i.e. in pooled analyses of two studies, or where the estimate of heterogeneity is equal to zero), we will use the Wald‐type method.
In the case of evidence of substantial or considerable statistical heterogeneity, we will not combine trial results in a meta‐analysis but instead present a narrative synthesis of results following the guidance in Chapter 12 of the Cochrane Handbook for Systematic Reviews of Interventions [39].
Investigation of heterogeneity and subgroup analysis
Investigation of heterogeneity
We will evaluate the overall characteristics of the studies included in the analysis, focusing specifically on the characteristics of the study participants, the type of interventions and the study design, in order to determine the level of clinical and methodological heterogeneity.
Prior to conducting meta‐analysis, we will evaluate heterogeneity by assessing the distribution of effect size estimates in the forest plots and calculating the I2 statistic to gauge the amount of total variability that can be attributed to heterogeneity amongst studies. With reference to Chapter 10 of the Cochrane Handbook for Systematic Reviews of Interventions [40], we will use the following thresholds when interpreting the I2 values.
0% to 40%: may not be important
30% to 60%: may represent moderate heterogeneity
50% to 90%: may represent substantial heterogeneity
75% to 100%: considerable heterogeneity
Subgroup analysis
Where sufficient data are available, we will conduct the following subgroup analyses.
Age (e.g. 50 years or less versus greater than 50 years)
Chemotherapy used (e.g. antimicrotubule agents (e.g. paclitaxel), topoisomerase inhibitors (e.g. doxorubicin), others)
Adherence to scalp‐cooling treatment (e.g. less than 80%, 81% duration of scalp cooling or greater)
Procedure used (a continuous cooling system versus another system)
Scalp skin temperature (18 °C or less versus greater than 18 °C) [41]
We will compare subgroups using the formal test for subgroup differences in RevMan, as described in Section 10.11.3.1 of the Cochrane Handbook for Systematic Reviews of Interventions [40].
Equity‐related assessment
We will not be able to investigate health inequities in this review. This is because the availability and cost of scalp‐cooling equipment is likely to vary widely across countries and hospitals, and each country will have its own reimbursement process if scalp cooling is available.
Sensitivity analysis
We plan to perform a sensitivity analysis for the critical outcomes to assess the effect of excluding studies with a high overall risk of bias. If we assess all studies to be at low risk of bias across all domains, we will not perform sensitivity analysis.
Certainty of the evidence assessment
We will prepare a summary of findings table for the primary comparison of scalp cooling versus no treatment to prevent hair loss. This table will present key information on the study population, interventions, and the following critical and important outcomes.
Hair loss induced by chemotherapy
Serious adverse events related to scalp cooling
Adherence to scalp cooling method
Adverse events related to scalp cooling
Scalp metastasis incidence
Quality of life
Financial burden
Two review authors (YK, KT) will evaluate the certainty of the evidence for each outcome according to the GRADE approach (risk of bias, inconsistency, imprecision, indirectness and publication bias) [34]. For each outcome, we will categorise the certainty of the body of evidence as 'high,' 'moderate,' 'low' or 'very low.' We will resolve any discrepancies by discussion or in consultation with a third review author (NY). We will report the reasons for all decisions to downgrade the certainty of the evidence from high.
If members of the authors of this review are also authors of any included studies for this review, these authors will not be involved in the risk of bias assessment for their own study or be involved in the GRADE assessment that uses outcome data from their own study.
Consumer involvement
Consumers were not involved in this protocol.
Consumers will be involved in the review process during the review stage to help ensure their perspectives are reflected in the final manuscript.
Supporting Information
Supplementary materials are available with the online version of this article: 10.1002/14651858.CD016196.
Supplementary materials are published alongside the article and contain additional data and information that support or enhance the article. Supplementary materials may not be subject to the same editorial scrutiny as the content of the article and Cochrane has not copyedited, typeset or proofread these materials. The material in these sections has been supplied by the author(s) for publication under a Licence for Publication and the author(s) are solely responsible for the material. Cochrane accordingly gives no representations or warranties of any kind in relation to, and accepts no liability for any reliance on or use of, such material.
Supplementary material 1 Search strategies
New
Additional information
Acknowledgements
Annabel Goodwin and Nicholas Wilcken (Co‐ordinating Editors), Melina Willson (Managing Editor), Ava Tan (Assistant Managing Editor, Information Specialist) and Peta Skeers (Information Specialist) from the Cochrane Breast Cancer Group supported the authors in the development of this protocol. This involved providing advice on clinical and methodological content, editing, devising search strategies, conducting searches on major medical databases and trial registers, nominating consumer and clinical peer reviewers for this review topic, and assisting authors with revising manuscripts following peer‐reviewer comments.
Editorial and peer‐reviewer contributions
The following people conducted the editorial process for this article.
Sign‐off Editor (final editorial decision): Rachel Dear, Senior Staff Specialist in Medical Oncology, St Vincent's Hospital Sydney. Associate Professor, UNSW Sydney Medicine & Health, Australia
Managing Editor (selected peer reviewers, provided editorial guidance to authors, edited the article): Gail Quinn, Cochrane Central Editorial Service
Editorial Assistant (conducted editorial policy checks, collated peer‐reviewer comments and supported editorial team): Lisa Wydrzynski, Cochrane Central Editorial Service
Copy Editor (copy editing and production): Andrea Takeda, Cochrane Central Production Service
Peer reviewers (provided comments and recommended an editorial decision): Dr Lorenzo Ala MD, La Sapienza, University of Rome (clinical/content review); Nuala Livingstone, Cochrane Evidence Production and Methods Directorate (methods review); Jo Platt, Central Editorial Information Specialist (search review)
Contributions of authors
YK: conceptualisation, methodology, writing – original draft, writing – review and editing. KT: methodology, writing – review and editing. KH, KI: writing – review and editing. NY: methodology, resources, writing – review and editing, supervision. HN, EO, TH: supervision, writing – review and editing. All authors reviewed and approved the final manuscript.
Declarations of interest
None of the authors have any commercial or non‐commercial conflicts of interest relevant to this review.
HN received a research fund from GlaxoSmithKline and consulting fees from GlaxoSmithKline, Sony, and Kowa, outside the submitted work.
Sources of support
Internal sources
-
None, Other
No internal source of support
External sources
-
None, Other
No external source of support
Registration and protocol
Cochrane approved the proposal for this review in June 2024.
Data, code and other materials
Data sharing is not applicable to this article as it is a protocol, so no datasets were generated or analysed.
Notes
Published notes in RevMan are for editor use only. Authors should leave this section blank.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary material 1 Search strategies
Data Availability Statement
Data sharing is not applicable to this article as it is a protocol, so no datasets were generated or analysed.