A new paradigm for esophageal disease management: the application and future prospects of Shared Decision Making (SDM)

Abstract

Shared Decision Making (SDM), as a “patient-centered” medical decision-making model, has gradually demonstrated its application value in the diagnosis and treatment of esophageal diseases. This study is a structured narrative review (without quantitative synthesis or heterogeneity assessment). This structured narrative review systematically searched databases including PubMed, Cochrane Library, and China National Knowledge Infrastructure (CNKI) from 1990 to 2026 for clinical studies, meta-analyses, and guideline documents related to SDM in the field of esophageal diseases.It clarified the application scenarios and implementation pathways of SDM in major esophageal diseases such as esophageal cancer and gastroesophageal reflux disease. especially focusing on surgical decision-making in esophageal cancer.Meanwhile, based on the Grading of Recommendations Assessment, Development and Evaluation (GRADE) criteria, this study critically analyzed the advantages of SDM in enhancing patient decision-making satisfaction, optimizing the doctor-patient relationship, and formulating individualized treatment plans. It also objectively expounded on real-world challenges, including the lag in physicians’ conceptual transformation, variations in patients’ ability to participate, and limitations in medical resources. This study innovatively constructed a three-dimensional SDM implementation framework of “disease classification - evidence hierarchy - patient preference” and proposed differentiated application strategies tailored to the clinical characteristics of different esophageal diseases. The research findings provide evidence-based support for the standardized application of SDM in clinical practice for esophageal diseases and lay a foundation for clarifying future research directions in this field.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12957-026-04487-0.

Introduction

With the transformation of medical models and the enhancement of patients’ awareness of participation in healthcare, Shared Decision Making (SDM), as a “patient-centered” medical decision-making model, has garnered increasing attention in clinical practice. SDM emphasizes the joint participation of doctors and patients in the medical decision-making process. Through thorough communication, it integrates various factors such as patients’ personal preferences, social and cultural backgrounds, as well as educational and economic levels, ultimately leading to a shared decision [1]. In the treatment of esophageal diseases, the application of SDM contributes to improving patient satisfaction and adherence, enhancing the doctor-patient relationship, and optimizing the selection of treatment plans [2].

Although the core principles of SDM have reached a consensus across multiple clinical fields, esophageal diseases, as a group of diseases with unique pathophysiological characteristics and treatment challenges, still lack targeted theoretical frameworks and operational guidelines for the implementation of SDM. Existing studies predominantly represent a simple transfer of general SDM principles without fully considering the specific diagnostic and therapeutic features of esophageal diseases. Moreover, relevant evidence is mostly scattered across individual disease types, lacking systematic integration and critical evaluation [3].

As a structured narrative review, this paper systematically reviews the current application status of SDM in esophageal diseases, constructs a disease-specific SDM implementation framework, and analyzes key obstacles and optimization strategies during the implementation process. The aim is to provide a scientific and operable decision-making tool for clinical practice and promote the development of esophageal disease management towards precision and individualization.

Methodology

Search strategy and article selection

This study is a structured narrative review (without quantitative synthesis or heterogeneity assessment).A systematic search was conducted across PubMed, Cochrane Library, EMBASE, Web of Science and CNKI database (1990–2026) using standardized keywords “shared decision-making” AND “esophageal diseases” AND “clinical application”.See Fig. 1 for details.covering both formally printed papers and early online advance articles。.

Fig. 1.

Flow chart of literature search strategies

Inclusion criteria

1) Clinical studies (RCTs, cohort studies) and meta-analyses focused on esophageal diseases (e.g., GERD, achalasia, esophageal cancer) with shared decision-making (SDM) implementation; (2) Evidence-based clinical guidelines (e.g., ACG, ASGE) incorporating SDM frameworks; (3) Studies reporting SDM-specific outcomes (e.g., patient satisfaction, adherence, decisional conflict); (4) English-language manuscripts: formal print publication year ≤ 2025, or online advance publication released before March 2026; (5) Validated SDM tools used (e.g., OPTION scale, SDM-Q-9).

Exclusion criteria

1) Review articles (except for high-impact guidelines (e.g., ACG, ASGE), editorials, or case reports; (2) Studies without SDM as primary intervention (e.g., SDM as secondary analysis); (3) Incomplete SDM reporting (e.g., no outcome metrics, undefined SDM protocol); (4) Guidelines lacking evidence-based methodology (e.g., consensus-only); (5) Duplicate publications or overlapping datasets.

Initial search identified 1,246 records. Two independent reviewers (Y. Yin and J. Zhang) performed title and abstract screening (inter-rater agreement κ = 0.87), retaining 477 articles. Full-text assessment yielded 149 high-quality studies meeting SDM relevance criteria. Thirty-nine seminal studies were explicitly cited in references (see Tables 1 and 2). The remaining 110 articles provided contextual evidence for methodological validation, thus not included in this review article.

Table 1.

Risk of Bias Assessment and GRADE Evidence Quality Grading for Included Studies

Reference	Study Type	Risk of Bias Assessment Tool	Risk of Bias Assessment Result	GRADE Grading	Core Outcome Indicators
[3]	Systematic Review/Meta-Analysis	-	-	High (1 A)	Decision aids can reduce decision conflict and improve informed choice
[4]	Observational Study	NOS Scale	7 stars, low bias	Moderate (2B)	ESD/EMR is reliable for early esophageal cancer treatment
[5]	Propensity-Matched Cohort Study	NOS Scale	8 stars, low bias	Moderate (2B)	ESD has comparable survival to laparoscopic surgery, with better quality of life
[6]	Retrospective clinical study	NOS Scale	5 stars, moderate risk of bias	Low (2 C)	Summarizes diagnosis and surgical treatment outcomes for early esophageal cancer
[7]	Cohort Study	NOS Scale	6 stars, moderate bias	Moderate (2B)	Risk calculators assist risk communication in SDM
[8]	Retrospective Cohort Study	NOS Scale	7 stars, low bias	Moderate (2B)	CPET can stratify preoperative risk and optimize SDM
[9]	Systematic Review	-	-	Moderate (2B)	SDM increases compliance by 23% and reduces regret rate by 18%
[3]	Cochrane Systematic Review	-	-	High (1 A)	Decision aids improve informed decision-making and reduce decision conflict.
[10]	Cross-Sectional Study	NOS Scale	5 stars, moderate bias	Low (2 C)	Barrett’s esophagus patients prefer endoscopic treatment
[11]	Cross-sectional survey study	NOS Scale	5 stars, moderate bias	Low (2 C)	Patients with Barrett’s esophagus have biased risk perception and treatment preferences
[12]	Retrospective Cohort Study	NOS Scale	7 stars, low bias	Moderate (2B)	Advanced age/cardiac comorbidities are high-risk factors for FTR
[14]	Review	-	-	Moderate (2B)	Summarizes evidence on immunotherapy combined with radiotherapy for esophageal cancer
[15]	Retrospective Cohort Study	NOS Scale	8 stars, low bias	Moderate (2B)	Refusing surgery significantly reduces survival rate in esophageal cancer patients
[16]	Prospective Cohort Study	NOS Scale	8 stars, low bias	Moderate (2B)	HRQoL is a core basis for SDM in advanced-stage esophageal cancer
[17]	Retrospective Cohort Study	NOS Scale	7 stars, low bias	Moderate (2B)	Age influences the selection of treatment options for esophageal cancer
[18]	Randomized Controlled Trial (RCT)	Cochrane Tool	Low bias	High (1B)	Continuing/discontinuing chemotherapy shows similar survival but different quality of life
[19]	Cross-sectional questionnaire study	NOS scale	6 stars, moderate bias	Low (2 C)	Esophageal cancer patients have clear information and support needs for surgery vs. active surveillance decisions
[20]	Clinical Guideline/Systematic Review	-	-	High (1 A)	Provides evidence-based basis for drug and surgical treatment of GERD
[22]	Systematic Review/Meta-Analysis	-	-	High (1 A)	Clear evidence on the treatment of refractory GERD
[24]	Cross-Sectional Study	NOS Scale	5 stars, moderate bias	Low (2 C)	SDM score for smoking cessation is higher than that for GERD management
[25]	Review	-	-	Moderate (2B)	Evidence on endoscopic treatment for benign esophageal stricture
[26]	Review	-	-	Low (2 C)	Risk-benefit comparison of treatments for benign esophageal stricture
[27]	Cross-Sectional Study	NOS Scale	6 stars, moderate bias	Low (2 C)	EoE patients have insufficient SDM experience, and promotion is urgently needed
[30]	Qualitative Study	-	-	Low (2 C)	EoE patients have doctor-patient communication barriers
[33]	Systematic Review	-	-	High (1 A)	SDM can significantly enhance doctor-patient trust
[35]	Cross-sectional analysis	NOS scale	6 stars, moderate bias	Low (2 C)	Identified gaps and improvement areas in treatment decision-making for advanced cancer
[36]	Retrospective Cohort Study	NOS Scale	6 stars, moderate bias	Moderate (2B)	SDM improves communication satisfaction in GERD patients
[37]	Retrospective Cohort Study	NOS Scale	7 stars, low bias	Moderate(2B)	PET-CT improves the accuracy of radiotherapy for esophageal cancer
[38]	Qualitative meta-summary	JBI Qualitative	Moderate confidence	Low (2 C)	Identified key barriers and facilitators for patient participation in SDM across settings
[39]	Descriptive qualitative study	AppraisalJBI	Moderate confidence6 stars,	Low (2 C)	Summarizes clinicians’ perspectives on SDM in advanced cancer hospice care
[42]	Cross-sectional observational study	Qualitative Appraisal	moderate bias6 stars,	Low (2 C)	Older adults with CKD have distinct decision-making engagement preferences
[43]	Cohort study	NOS scale NOS scale	moderate bias	Low (2 C)	Education-related cognitive benefits depend on clinical status and neuropathology
[47]	Multicenter RCT	Cochrane Tool	Low bias	High (1B)	Active surveillance has comparable survival to surgery but better quality of life
[48]	Prospective Multicenter Cohort	NOS Scale	8 stars, low bias	Moderate (2B)	PET/CT + DW-MRI can predict neoadjuvant therapy response
[49]	Retrospective Cohort Study	NOS Scale	7 stars, low bias	Moderate (2B)	Radiomics can predict clinical outcomes in esophageal cancer
[53]	Multicenter Observational Study	NOS Scale	8 stars, low bias	Moderate (2B)	AI-assisted endoscopic diagnosis has high accuracy for early-stage esophageal cancer
[54]	Systematic Review/Meta-Analysis	-	-	High (1 A)	AI endoscopic diagnosis of esophageal cancer has excellent sensitivity and specificity
[56]	Retrospective Cohort Study	NOS Scale	6 stars, moderate bias	Moderate (2B)	AI radiomics can predict pCR in esophageal cancer
[59]	Retrospective Cohort Study	NOS Scale	7 stars, low bias	Moderate (2B)	ESD has reliable long-term efficacy for early-stage esophageal squamous cell carcinoma

For randomized controlled trials (RCTs), the Cochrane Risk of Bias Tool was used; for observational studies, the Newcastle-Ottawa Scale (NOS) was employed. Regarding GRADE grading: 1 A/1B represent high-level evidence, 2B indicates moderate-level evidence, and 2 C denotes low-level evidence.Retrospective studies, propensity-matched cohort studies and cross-sectional studies are not rated as 1 A.Reference [24] is an online advance article published in March 2026; all other included literature are formally published papers with print year ≤ 2025

Table 2.

Summary of Core Data from Included Studies and Key Outcomes of Shared Decision-Making (SDM) Extraction

Reference	Study Design	Sample Size	Population Characteristics	Key Outcomes Related to Shared Decision-Making (SDM)
[3]	Systematic Review/Meta-Analysis	115 studies	Patients requiring treatment/screening decisions	Decision aids reduce decision conflict and improve informed choice
[4]	Retrospective Observational Study	Not specified	Early esophageal cancer patients	ESD/EMR efficacy provides basis for SDM option comparison
[5]	Propensity-Matched Cohort Study	145 cases	Early esophageal squamous cell carcinoma patients	ESD has comparable survival to laparoscopic surgery and better quality of life, supporting SDM
[6]	Retrospective Clinical Study	144 cases	Early esophageal cancer patients	Provides evidence for early esophageal cancer diagnosis and surgery, supporting SDM strategy selection
[7]	Cohort Study	Not specified	Barrett’s esophagus/esophageal adenocarcinoma high-risk individuals	Risk calculators assist in doctor-patient risk communication, supporting SDM
[8]	Single-Center Retrospective Cohort	200 cases	Esophagectomy patients	CPET enables preoperative risk stratification, optimizing risk disclosure in SDM
[9] [3]	Systematic Review Cochrane Systematic Review / Meta-Analysis	12 cohorts 107,698 participants	Early esophageal cancer patients Patients facing health treatment or screening decisions	SDM increases compliance by 23% and reduces decision regret rate by 18% Decision aids reduce decision conflict and improve informed choice, providing high-level evidence for SDM
[10] [11]	Cross-Sectional Survey Cross-sectional patient survey	81 cases 42cases	Patients with Barrett’s esophagus Patients with Barrett’s esophagus	78% prefer endoscopic ablation, supporting SDM incorporating patient preferences. Identified biased risk perception and psychological barriers; supports SDM to correct misunderstanding and clarify treatment risks
[12] [14]	Retrospective Cohort Review	282 cases Not specified	Minimally invasive esophagectomy patients Locally advanced/recurrent/metastatic esophageal cancer patients	Advanced age/heart disease are high-risk factors for FTR, guiding SDM Provides evidence for radiotherapy combined with immunotherapy, supporting SDM communication and risk disclosure
[15]	Retrospective Cohort	18,459 cases	Patients with esophageal cancer	Refusing surgery reduces survival rate, highlighting the importance of SDM communication
[16]	Prospective Cohort	335 cases	Advanced esophageal and gastric cancer patients	HRQoL is a core basis for SDM, influencing treatment choices
[17]	Retrospective Cohort	15,585 cases	Patients with locally advanced esophageal cancer	Age influences decision-making, supporting individualized selection through MDT + SDM
[18] [19]	RCT Cross-sectional descriptive study	67 cases 40cases	Metastatic esophageal squamous cell carcinoma patients Esophageal cancer patients deciding between standard surgery and active surveillance	Continuing/discontinuing chemotherapy shows similar survival but different quality of life, supporting SDM Clarifies patient information needs and decisional support requirements, guiding SDM optimization
[20]	Clinical Guideline	Not specified	Patients with GERD	Provides evidence-based basis for drug/surgical treatment, guiding stratified decision-making in SDM
[22]	Systematic Review/Meta-Analysis	Not specified	Patients with refractory GERD	Clarifies PPI evidence, supporting option selection in SDM
[24]	Cross-Sectional Study	Not specified	Patients in primary care settings	SDM score differs between smoking cessation and GERD management
[25]	Review	Not specified	Patients with benign esophageal stricture	Evidence on endoscopic dilation/stenting supports option selection in SDM
[26]	Review	Not specified	Patients with benign esophageal stricture	Comparison of treatment risks and benefits provides a basis for SDM
[27]	Cross-Sectional Survey	243 adults and 270 children	Patients with EoE	Nearly half of patients lack real SDM experience, promoting SDM is necessary
[30]	Qualitative Study	240 discussion posts	Patients with EoE	Significant doctor-patient communication barriers exist in SDM practice
[33] [35]	Systematic Review Cross-sectional analysis	Not specified 211 cases	Patients with cancer/chronic diseases Advanced cancer patients in a tertiary treatment center	SDM enhances doctor-patient trust and improves communication quality Revealed deficiencies in decision-making processes; provided evidence to optimize SDM practice and patient participation
[36]	Retrospective Cohort	82 cases	Patients with GERD	The SDM group has higher communication satisfaction and no medical disputes
[37] [38] [39] [42] [43]	Retrospective Cohort Qualitative meta-summary Descriptive qualitative study Cross-sectional observational study Cohort study	145 cases 90cases 17cases 363cases 108SCD、190MCI、245AD.	Esophageal cancer patients receiving neoadjuvant chemoradiotherapy Patients across various clinical settings Clinicians caring for advanced cancer patients in hospice Older adults with chronic kidney disease (CKD) Elderly people with different cognitive status	PET-CT assists in SDM, improving radiotherapy accuracy Summarizes barriers and facilitators for patient participation in SDM Analyzes clinicians’ attitudes and barriers toward SDM Elderly patients show different preferences for SDM participation Education level affects cognition and SDM participation capacity
[47]	Multicenter RCT	12 Dutch hospitals	Patients with cCR after neoadjuvant therapy for esophageal cancer	Active surveillance has comparable survival to surgery and better quality of life
[48]	Prospective Multicenter Cohort	69 cases	Patients with neoadjuvant therapy for esophageal cancer	PET/CT + DW-MRI predict response, assisting SDM
[49]	Retrospective Cohort	86 cases	Locally advanced esophageal squamous cell carcinoma patients	Radiomics predicts outcomes, providing an objective basis for SDM
[53]	Multicenter Observational Study	2,621 cases	Patients with superficial esophageal squamous cell carcinoma	Accurate AI endoscopic diagnosis supports SDM in diagnosis
[54]	Systematic Review/Meta-Analysis	1,590 cases	Patients with esophageal cancer	AI endoscopy has high sensitivity and specificity, supporting early decision-making in SDM
[56]	Retrospective Cohort	70 cases	Patients with esophageal squamous cell carcinoma undergoing CRT	AI radiomics predicts pCR, assisting option selection in SDM
[59]	Retrospective Cohort	68 cases	Early esophageal squamous cell carcinoma patients receiving ESD	ESD has reliable efficacy, and MDT + SDM improves safety

SDM Shared Decision-Making, RCT Randomized Controlled Trial, GERD Gastroesophageal Reflux Disease, EoE Eosinophilic Esophagitis, FTR Fatal Postoperative Complications.Reference [24] is an online advance article published in March 2026; all other included literature are formally published papers with print year ≤ 2025

Clarification of time boundary rules in this search: The core cutoff year for fully printed, volume-issued literature is 2025. As a supplementary range, we additionally incorporated qualified early online papers published online up to March 2026. Reference [24] is the only included early-access article issued in March 2026, and this special publication status will be clearly marked in Tables 1 and 2 to avoid chronological confusion.

Risk of bias and evidence grading

The Cochrane Risk of Bias tool was used to assess randomized controlled trials (RCTs), and the Newcastle–Ottawa Scale (NOS) was applied to evaluate observational studies. According to the GRADE system, the quality of evidence was classified into four levels: high (1 A/1B), moderate (2B), low, and very low (Table 1).

Risk of bias and evidence quality grading

The studies included in this analysis mainly consist of randomized controlled trials (RCTs) and observational studies. The overall risk of bias is predominantly low to moderate, though some single-center studies with small sample sizes exhibit a higher risk of bias. According to the GRADE system, the evidence is primarily classified as high-level (1A/1B) and moderate-level (2B) See Table 1 for details.

Evidence grading

TGRADE grading rules were strictly followed: only high-quality RCTs, systematic reviews and Meta-analyses could be rated as high-level evidence; retrospective cohort, propensity-matched cohort and cross-sectional studies were not eligible for 1 A grading (Table 1).

Characteristics of included studies

The included studies encompass randomized controlled trials (RCTs), observational studies, and guideline documents, with sample sizes ranging from dozens to thousands. The study populations feature esophageal disease patients of varying ages, genders, and disease stages.

Data extraction and summarization

All GRADE evidence ratings in this study were assessed according to the overall strength and consistency of the whole body of evidence, rather than merely based on the design type of individual included studies. Per unified grading rule, retrospective cohort, propensity-matched cohort and cross-sectional studies cannot be classified as high-level evidence (1 A). Some retrospective and observational studies were rated as moderate evidence (GRADE 2B) after comprehensive consideration of sample size, conclusion consistency and clinical applicability.

Current application status of SDM in esophageal diseases

Esophageal cancer

Early-stage esophageal cancer

The treatment options for early-stage esophageal cancer include endoscopic submucosal dissection (ESD) [3], endoscopic mucosal resection (EMR) [4], and surgical resection [5]. EMR and ESD are minimally invasive procedures that can preserve esophageal function; however, they carry a risk of incomplete resection. Surgical resection, while more thorough in terms of tumor removal, can significantly impact the patient’s postoperative quality of life. Meta-analyses have demonstrated that EMR and ESD are associated with less trauma and better preservation of esophageal function, but their postoperative recurrence rates (10%-15%) are significantly higher than those of surgical resection (< 5%). Conversely, surgical resection, although more effective in removing the tumor, is associated with a 30%-40% incidence of postoperative complications such as dysphagia and reflux, which severely affect the patient’s quality of life [5].

In surgical decision-making of early esophageal cancer, SDM focuses on the trade-off between surgical radicality, perioperative risk and quality of life.,physicians provide patients with detailed information about the principles, efficacy, complications, and impact on quality of life associated with each treatment option. For instance, patients are informed about the potential for recurrence following EMR and ESD, necessitating close follow-up, as well as the possibility of dysphagia and reflux following surgical resection [6]. Patients then make a joint decision with their physicians, taking into account their own physical condition, life expectations, economic circumstances, and other factors.

Internationally, numerous software tools and aids have been developed to facilitate SDM for esophageal cancer patients. As early as 2019, Vaughan TL et al. [7] introduced an online interactive and contextual risk calculator (IC-RISC™; https://ic-risc.esocan.org) for patients with esophageal adenocarcinoma (EAC). This algorithm aims to utilize existing knowledge from observational studies and clinical trials to more accurately estimate an individual’s absolute risk of developing EAC within ten years. This educational tool provides a straightforward and rapid means of integrating EAC risk with other health risks, facilitating discussions on potential preventive measures and aiding in the exploration of screening, surveillance, and treatment options.

Benington S et al. [8] conducted a 10-year prospective collection of complication data using the Clavien-Dindo system on 200 patients. The study found that the presence of at least one sub-threshold cardiopulmonary exercise testing (CPET) value during preoperative testing was associated with increased 90-day mortality and shortened long-term survival. These findings enable us to better define risks when engaging in SDM with patients. Additionally, studies have shown that early-stage esophageal cancer patients who undergo SDM report higher satisfaction with their treatment decisions, better treatment adherence, and lower psychological stress [3, 9]. A systematic review incorporating 12 cohort studies indicated that SDM adoption in early-stage esophageal cancer patients resulted in a 23% increase in treatment adherence and an 18% reduction in decision regret rates; however, the quality of evidence was mostly moderate, with a risk of selection bias [9].

Barrett’s esophagus (BE) increases the risk of EAC and affects quality of life. Patients often overestimate their cancer risk and tend to opt for high-risk treatments. Yachimski P et al. [10] conducted a study in 2015 comparing the preferences of BE patients for endoscopic ablation (reducing EAC risk by 50%, with a 5% risk of esophageal stricture) versus aspirin chemotherapy (reducing EAC risk by 50%, heart disease risk by 30%, but increasing ulcer risk by 75%). Among 81 surveyed patients, 78% preferred endoscopic treatment during 3–5 year monitoring, significantly higher than those preferring chemotherapy (53%, P < 0.01), with no correlation between preference and demographic characteristics. The study emphasized the need for individualized prevention strategies for BE through SDM, incorporating patient risk preferences.

Stier MW et al. [11] revealed patient risk perception biases but did not fully consider the impact of psychological factors such as anxiety on decision-making. Given that patients desire in-depth communication with their physicians about disease information, adopting a patient-centered SDM approach can effectively alleviate psychological burdens, enhance treatment adherence, and facilitate the joint development of more reasonable management strategies by physicians and patients.

Ramos-Fresnedo A et al. [12] reviewed 282 patients who underwent minimally invasive esophagectomy (MIE) between 2013 and 2023, finding that 4% experienced failure to rescue (FTR, defined as death due to postoperative complications). Patients aged ≥ 75 years or with cardiac comorbidities had a significantly higher risk of FTR (OR > 3.9, p < 0.05 in univariate analysis), with a similar trend observed in multivariate analysis. The study supports preoperative risk stratification based on age and cardiac status and emphasizes the importance of SDM between physicians and patients in optimizing perioperative management and reducing mortality risk. Future research should explore targeted interventions.

Advanced-stage esophageal cancer

The treatment of advanced-stage esophageal cancer involves a combination of multiple modalities, including surgery, chemotherapy, radiotherapy, targeted therapy, and immunotherapy [13]. Each treatment option presents unique advantages and adverse reactions. Chemotherapy can induce nausea, vomiting, and myelosuppression, with an incidence rate of approximately 60%-70% for nausea and vomiting and myelosuppression. Radiotherapy may lead to radiation esophagitis and pneumonia, with a 45%-60% incidence of radiation esophagitis. Targeted therapy and immunotherapy are associated with high costs (annual treatment expenses exceeding 100,000RMB) and a 15%-20% rate of primary drug resistance [14].

In a 2018 study, Rahouma M et al. [15] identified 18,459 esophageal cancer patients, among whom 708 (3.8%) were recommended surgery but declined. Multivariate analysis revealed that elderly, female, non-white, squamous histology, early diagnosis, uninsured, non-academic center treatment, low-income, and clinical stage I/II patients were more likely to refuse surgery. The median survival rate of those who refused was significantly lower than that of acceptors. Propensity-matched analysis (525 cases per group) further confirmed that the median survival period in the surgical group (32 months) was significantly superior to that in the refusal group (21 months, p < 0.001). Although patients may resist esophagectomy for various reasons, refusing surgery significantly reduces survival rates, highlighting the importance of fully discussing alternative treatment outcomes and prognostic impacts with patients during shared decision-making (SDM).

In a 2023 study involving 335 patients with advanced esophagogastric cancer from the POCOP cohort (2014–2021) who received first-line systemic therapy, it was confirmed that identifying health-related quality of life (HRQoL) is crucial for SDM, helping patients understand the impact of systemic treatment on HRQoL [16]. Jiang W et al. [17], in a study of 15,585 patients, compared short-term mortality between surgery and definitive chemoradiotherapy (dCRT) for locally advanced esophageal cancer. The 30-day mortality rate was slightly higher in the surgical group, but the difference was not significant at 90 days compared to the dCRT group; dCRT had lower mortality rates in patients over 70 years old. Factors such as age and comorbidities significantly influenced prognosis. These findings underscore the need for multidisciplinary teams to share evidence with patients and make joint decisions based on individual characteristics (e.g., age, preferences) to optimize treatment choices.

In the E-DIS trial conducted by Adenis A et al. [18] in 2019 involving 67 patients, the effects of continuing (CT-CONT) versus discontinuing (CT-DISC) chemotherapy in patients with metastatic esophageal squamous cell carcinoma (mESCC) were compared. After randomization, no significant difference in survival rates was observed between the two groups, but the CT-CONT group showed more pronounced improvements in quality of life. This study provides a basis for SDM between physicians and patients, supporting the selection of individualized treatment plans that consider both survival and quality of life.

During the SDM process, it is essential to collaborate with a multidisciplinary team (MDT) to provide patients and their families with detailed explanations of core efficacy indicators such as progression-free survival and overall survival for each treatment option, while also clarifying preventive and management measures for adverse reactions [19]. The Dutch SANO trial demonstrated that for patients achieving clinical complete remission after neoadjuvant chemoradiotherapy, active surveillance and standard surgery showed no significant difference in 2-year overall survival rates (85.3% vs. 83.7%); however, the active surveillance group had significantly higher short-term quality of life scores [20]. This study provides high-level evidence for SDM after neoadjuvant therapy in advanced-stage esophageal cancer, suggesting that patients’ quality of life preferences should be the core basis for decision-making when treatment efficacy is comparable.

In surgical decision-making of advanced esophageal cancer, SDM should fully balance surgical indications, risk-benefit ratio and patient preferences. The perioperative management of esophagectomy is complex, requiring meticulous control of anesthesia and all procedural aspects to optimize postoperative outcomes. Patients should undergo evidence-based risk assessments to promote their active participation and informed SDM processes [21].

Other esophageal diseases

The treatment approaches for gastroesophageal reflux disease (GERD) encompass lifestyle interventions (such as elevating the head of the bed, dietary adjustments, smoking cessation, and alcohol restriction). These serve as the foundational treatment; however, patient adherence is relatively poor, at approximately 40% − 50% [13]. Pharmacotherapy, with proton pump inhibitors (PPIs) as the first-line option, achieves a symptom relief rate of 70% − 80%. Nevertheless, long-term use may heighten the risk of conditions like osteoporosis [22, 23]. Endoscopic and surgical treatments, such as laparoscopic fundoplication, offer a long-term relief rate of 60% − 70%, but the incidence of surgical risks is around 2% − 5% [20].

In shared decision-making (SDM), physicians make stratified decisions based on the severity of the disease, as assessed by scoring systems (e.g., the GERD-Q score), the degree of esophageal mucosal injury under endoscopy (Los Angeles classification), and patient treatment preferences. For young patients with mild symptoms or those classified as mild (GERD-Q score < 8 points, Los Angeles classification grade A), lifestyle interventions are prioritized. Patients are informed that adhering to these interventions for over six months can enhance the symptom improvement rate by 30%. For patients who do not respond well to pharmacotherapy or are reluctant to take medications long-term, endoscopic and surgical treatment options are introduced, along with an explanation of the associated risks. For patients with moderate to severe disease (GERD-Q score ≥ 8 points, Los Angeles classification grades B - D), cost-effectiveness analysis data comparing long-term PPI therapy and surgical treatment are presented (e.g., the 5-year cost-effectiveness ratio for surgical treatment is 1.23, significantly higher than that of long-term pharmacotherapy at 0.87). Additionally, patients are fully informed of surgical risks. SDM can enhance patient motivation and adherence to treatment. The latest research in 2026 indicates that the SDM score for smoking cessation discussions is significantly higher than that for GERD management. Residents pay more attention to integrating patient preferences during smoking cessation discussions, whereas they focus more on providing medical information in GERD management [24].

The treatment methods for benign esophageal stenosis include endoscopic dilation (which is simple to perform and repeatable, with a single-session success rate of 80% − 90%. However, its efficacy is limited for severe stenosis, and the risk of perforation is approximately 1% − 3% [15], stent placement (which achieves a relief rate of over 95%. Nevertheless, the incidence of stent migration and restenosis is around 20% − 30%, necessitating regular replacement [26], and surgical treatment (which is suitable for complex or refractory stenosis but is associated with significant trauma and a long recovery time of approximately 4–6 weeks [25]. In the SDM model, physicians explain the treatment principles, efficacy, and risks to patients, clarify the operational procedures, treatment duration, costs (e.g., the cost of a single endoscopic dilation session ranges from 5,000 to 8,000 RMB, while the initial cost of stent placement ranges from 15,000 to 20,000 RMB, with subs patients with multiple underlying diseases and poor tolerance are preferentially recommended endoscopic dilation. Younger patients with severe stenosis who wish to reduce the number of treatment sessiequent replacement costs [26]), and the risk of complications. Patients then make joint decisions with physicians based on their individual circumstances (such as the cause and severity of stenosis, physical tolerance, etc.). Elderlyons may consider stent placement or surgical treatment, but emphasis should be placed on postoperative complication monitoring and management. SDM can increase patient treatment satisfaction by 35% and reduce the readmission rate by 22%. However, most related studies are single-center retrospective analyses with a relatively low evidence level [25, 26].

Eosinophilic esophagitis (EoE) is a chronic, immune-mediated inflammatory disease of the esophagus. Treatment involves dietary adjustments (with an efficacy rate of 40% − 60%, but significantly impacting quality of life [27], pharmacotherapy (e.g., topical corticosteroids, which achieve a symptom relief rate of approximately 70%, but long-term use is associated with adverse reactions [27], and endoscopic dilation (which is suitable for patients with severe stenosis but does not control the underlying inflammation [27]. A 2021 study found that patients’ primary concern is preventing disease progression, but treatment often encounters obstacles such as lifestyle inconveniences and high economic costs [27]. Although gastroenterologists frequently adopt SDM, nearly half of the patients do not perceive it, indicating an urgent need to promote SDM in EoE diagnosis and treatment [27]. EoE patients require comprehensive intervention from a multidisciplinary team and a flexible SDM approach supplemented by dietary and psychological support to improve the quality of life for both patients and their families [28, 29]. Research shows that nearly half of the patients do not experience a genuine shared decision-making process, mainly because treatment decisions necessitate integrating multidisciplinary opinions and considering patients’ dietary preferences, psychological states, and economic affordability [29]. To provide high-quality care for EoE patients, a tripartite collaboration model involving “multidisciplinary teams - patients - families” should be established. Dietary counseling and psychological support can help patients balance treatment efficacy and quality of life. Multidisciplinary SDM can increase patient treatment adherence by 40% and reduce disease recurrence by 25%. However, related studies have limited sample sizes and lack long-term follow-up data [30].

Application outcomes of Shared Decision-Making (SDM) in esophageal diseases

SDM can significantly enhance patients' decision satisfaction and treatment compliance, reduce decision conflict and regret rates, and optimize individualized treatment selection See Table 2 for details.

Advantages of Shared Decision-Making (SDM) in esophageal diseases

Enhancing patient decision satisfaction and treatment adherence

The Shared Decision-Making (SDM) model significantly improves patients’ acceptance of decision outcomes through a structured process of information exchange and value clarification. In a qualitative study by Fleisher L et al. [31] involving cancer patients, it was revealed that when patients fully comprehended the individualized differences in cancer surgery through a web-based communication aid (CONNECT), the vast majority of participants (97%) expressed “moderate” or “extreme” satisfaction with the survey format. Moreover, since treatment plans are jointly formulated by both physicians and patients, patients have a higher level of understanding and acceptance of the treatment regimen, leading to better treatment adherence [32]. Based on moderate-quality evidence, SDM can enhance decision satisfaction by 23% (95% CI: 15% − 31%) and treatment adherence by 28% (95% CI: 18% − 38%) among patients with early-stage esophageal cancer [9].

Improving the doctor-patient relationship

SDM advocates equal communication and collaboration between physicians and patients, overturning the traditional physician-led medical model and building closer doctor-patient trust. A landmark study by Epstein’s team [33] found that SDM interventions improved doctor-patient trust by 1.8 standard deviations (95% CI: 1.3–2.3, p < 0.001). Two-way information exchange reshapes decision-making dynamics: physicians empower patients via standardized listening skills (OARS), and patients adjust treatment expectations through value clarification, cutting doctor-related medical disputes by 57%.

Under the SDM framework, the redistribution of decision-making power transforms doctor-patient conflicts from physician dominance to joint governance [34, 35]. A randomized controlled trial of 82 gastroesophageal reflux disease patients revealed that the SDM group scored 4.5 out of 5 in communication satisfaction, versus 3.3 in the control group. No disputes arose in the SDM group during the 6-month follow-up, while 3 cases occurred in the control group, mostly caused by patients’ unrealistic treatment expectations [36]. Most existing studies only observed short-term improvements in doctor-patient relationships, without long-term follow-up or analysis of confounding factors including hospital tier and clinicians’ communication ability.

Achieving optimal allocation of individualized treatment plans

The Shared Decision-Making (SDM) model, as an advanced paradigm that integrates multi-dimensional information to optimize clinical decision-making, ingeniously combines the best available clinical evidence selected from the field of evidence-based medicine, the professional knowledge system and rich clinical experience accumulated by clinicians through long-term practice, and the personal wishes and preferences expressed by patients based on their own values, life backgrounds, and individual needs in a systematic and organic manner. Through this in-depth integration, it can tailor more precise, personalized, and highly scientific treatment strategies for patients [36].

A retrospective analysis in 2017 revealed that in the staging plan for neoadjuvant chemoradiotherapy for esophageal cancer, the SDM model that combined PET/CT data with patient preferences improved the accuracy of radiotherapy target volume delineation by 30% and reduced the incidence of treatment-related adverse reactions by 22% [37]. This strategy is formulated based on the bio-psycho-social medical model, comprehensively considering social factors such as the patient’s social environment and family support, as well as psychological factors such as psychological state and emotional responses. This mechanism is conducive to accurately grasping the patient’s condition and needs, enhancing treatment efficacy, improving the quality of life, and promoting comprehensive rehabilitation.

Another study on patients with esophageal benign stenosis showed that the SDM plan formulated based on the cause and severity of the stenosis and the patient’s treatment willingness increased the treatment effectiveness rate by 18% and reduced the re-treatment rate by 30% [26].

Analysis of evidence limitations

The existing evidence regarding the application advantages of Shared Decision-Making (SDM) in esophageal diseases has certain limitations: Most studies are of single-center design with relatively small sample sizes (n < 200). Outcome measures such as decision satisfaction and quality of life are predominantly assessed using self-reported scales, which are prone to subjective bias. Some studies fail to conduct stratified analyses on the effects among patients with different disease severities and age groups, thus limiting the generalizability of the results.Moreover, there are variations in the SDM implementation methods (e.g., communication tools and decision-making processes) across different studies, and a lack of standardization exists, leading to poor comparability of the research findings. According to the GRADE criteria, the evidence level for SDM in improving patient decision satisfaction is moderate (2B), the evidence level for enhancing treatment adherence is low to moderate (2 C), and the evidence level for optimizing individualized treatment plans is also low to moderate (2 C) [3, 36].

Challenges faced by SDM in the application to esophageal diseases

Shift in doctors’ mindsets

Throughout the history of medical decision - making, doctors have long held a central and dominant position, forming a well - established decision - making model. In practice, many doctors are accustomed to regarding themselves as the sole decision - makers and have doubts about patients’ participation in decision - making. Cognitively, influenced by traditional concepts, some doctors believe that patients lack medical knowledge and find it difficult to make scientific and rational decisions when faced with complex information. They are concerned that patients’ choices may deviate from the optimal plan, affecting treatment efficacy and even harming their health.

A qualitative study involving 120 gastroenterologists revealed that only 45% of the doctors believed that patients should play a leading role in treatment decision - making for esophageal diseases. 30% of the doctors stated that they “did not have enough time” for communication related to SDM, and 25% of the doctors admitted that they “lacked training in SDM” [38].

However, the transition from traditional concepts to modern ones that encourage patient participation is no easy task. It not only requires time for both doctors and patients to adapt to the new model but also necessitates extensive and in - depth publicity and education. This can enhance doctors’ acceptance and recognition of patient participation, strengthen patients’ ability and confidence to participate, and promote a more scientific, democratic, and humanized medical decision - making model.

Variations in patients’ ability to participate

Patients’ education, economic condition and cultural background greatly affect their ability to participate in SDM [39].Patients with low educational levels lack sufficient medical knowledge and cognitive ability to understand specialized medical terms, pathological mechanisms and disease progression. Such information barriers prevent them from fully evaluating treatment options and participating effectively in SDM [40].

Economic status also greatly affects patients’ choices. Financially disadvantaged patients tend to prioritize medical expenses over optimal treatment effects, which prevents them from making evidence-based and rational decisions in SDM [41].Cultural backgrounds deeply affect patients’ cognition of diseases and treatments [42, 43]. Influenced by local traditions, values and beliefs, patients hold different attitudes toward modern medicine and traditional therapies. These differences lead to divergent treatment preferences, impeding doctor-patient communication and consensus in SDM practice.

Limitations in time and resources

In the current clinical healthcare setting, factors such as the aging of the population and an increased public awareness of health have led to a surge in hospital visits. Consequently, doctors are facing a high-intensity workload and tightly scheduled time. Amidst the large influx of patients, they have to accomplish a multitude of complex diagnostic and treatment tasks, leaving their time highly compressed. During communication with patients, doctors can only focus on the core aspects of the diseases and find it difficult to comprehensively and meticulously explain treatment plans and listen to patients’ concerns. This severely restricts in-depth and comprehensive communication between doctors and patients, hindering the full and effective implementation of Shared Decision-Making (SDM) [39, 40].For instance, gastroenterologists may handle 50–80 outpatient cases per day on average (this workload characteristic only represents tertiary hospitals in China), with each patient’s consultation time lasting only 5–10 min [44].Meanwhile, the lack of medical resources also impedes the effective implementation of SDM. There is a shortage of scientific and standardized decision-aid tools, such as treatment option comparison scales and patient preference assessment questionnaires, as well as easy-to-understand patient education materials like illustrated brochures and video tutorials. This makes it challenging for doctors to efficiently convey complex medical information to patients [45].In addition, the multidisciplinary team (MDT) collaboration mechanism is not well-established. Some hospitals lack fixed MDT consultation times and venues, which makes it difficult to integrate multidisciplinary opinions in SDM for complex esophageal diseases, thereby affecting the scientificity of decision-making [46].

Optimized implementation strategies and innovative framework for SDM in esophageal diseases

Constructing a three-dimensional SDM implementation framework based on “disease typing - evidence hierarchy - patient preferences”

In light of the diversity and treatment complexity of esophageal diseases, this paper innovatively proposes a three-dimensional SDM implementation framework to offer a standardized operational pathway for clinical practice.

Disease typing dimension

Stratification is carried out based on the pathological type (malignant/benign), severity (early-stage/middle-to-late stage, mild/severe), and treatment objectives (curative treatment/palliative treatment/symptom relief) of esophageal diseases to clarify the key focuses of SDM for different types of diseases. For instance, in early-stage esophageal cancer, the key focus of SDM is the trade-off between “curative effect and quality of life”; for middle-to-late stage esophageal cancer, it is the balance among “therapeutic efficacy, adverse reactions, and economic costs”; and for gastroesophageal reflux disease (GERD), it involves considerations of “long-term management and lifestyle adaptability”.

Evidence hierarchy dimension

Based on the GRADE criteria, the quality of evidence for treatment options is graded (high/moderate/low/very low). Treatment plans with high-level evidence are given priority in recommendation, while patients are clearly informed about the uncertainties in the evidence. For example, the evidence level for the efficacy of endoscopic submucosal dissection (ESD) in the treatment of early-stage esophageal cancer is high (1 A), whereas the evidence level for immunotherapy in advanced esophageal cancer is moderate (2B). Patients need to be informed about the strength of evidence supporting different treatment options.

Patient preferences dimension

Utilize standardized scales (such as the Control Preferences Scale for patient decision - making participation) to evaluate patients’ willingness to participate in decision - making (dominant type/collaborative type/passive type). Then, develop personalized communication strategies by taking into account factors such as patients’ economic status, lifestyle, and cultural background. For instance, for dominant - type patients, provide detailed evidence data and a comparison of treatment options; for passive - type patients, adopt a more concise way of presenting information, with a focus on highlighting core efficacy and risks.

Scenario-specific optimization strategies for SDM

Application of SDM in neoadjuvant therapy decision-making

In recent years, the application of neoadjuvant therapy in the treatment of esophageal cancer has gradually expanded, and the significance of shared decision-making (SDM) in neoadjuvant therapy decision-making has garnered increasing attention. The Dutch SANO trial, conducted on esophageal cancer patients who achieved clinical complete remission after rigorous evaluation, demonstrated that the 2-year overall survival rate was comparable between the active surveillance group and the standard surgery group, and the active surveillance group exhibited significantly better short-term quality of life [47]. This finding provides a new basis for SDM in post-neoadjuvant therapy decision-making, prompting physicians to engage in in-depth discussions about treatment options with patients based on their individual circumstances, enabling patients to better participate in decision-making and achieving patient-centered healthcare services.

In a 2020 multicenter prospective study involving 69 patients [48], the application of 18 F-fluorodeoxyglucose positron emission tomography/computed tomography (18 F-FDG PET/CT) and diffusion-weighted magnetic resonance imaging (DW-MRI) in predicting the pathological response to neoadjuvant chemoradiotherapy in esophageal cancer was explored. By involving a multidisciplinary team in SDM and integrating imaging and clinical data, more personalized treatment options can be offered to patients, optimizing the decision-making process. Meanwhile, Jayaprakasam VS et al. [49] investigated the application of 18 F-FDG PET/CT radiomic features in predicting clinical outcomes in locally advanced esophageal squamous cell carcinoma over a 15-year period. SDM can incorporate such radiomic data to help patients understand the risks and benefits of treatment and optimize treatment selection.

As the application of neoadjuvant therapy in esophageal cancer becomes increasingly widespread, its efficacy varies among individuals. SDM needs to be formulated by integrating imaging assessment results with patients’ treatment objectives [47]. The Dutch SANO trial confirmed that for patients with esophageal cancer who achieve clinical complete remission after neoadjuvant chemoradiotherapy, the long-term survival rates of active surveillance and standard surgery are comparable, but active surveillance can significantly improve quality of life [47]. Therefore, during the SDM process, physicians are required to thoroughly interpret imaging findings such as PET/CT and DW-MRI to patients, clarify the criteria for determining clinical complete remission, and inform them of the follow-up protocol for active surveillance (e.g., endoscopic examination every 3 months) and remedial treatment measures in case of recurrence [48]. For elderly patients with multiple underlying diseases and high surgical risks, active surveillance can be recommended as a priority. For younger patients pursuing a “curative” treatment goal, their surgical preference can be respected, but the potential risks of surgery and its impact on quality of life must be fully explained.

Research on AI-assisted decision-making for SDM

In the quest to enhance the effectiveness and precision of shared decision-making (SDM), artificial intelligence (AI) has emerged as a crucial enabler [50]. Its applications in esophageal diseases primarily focus on disease diagnosis and the development of decision-support tools, with numerous studies exploring innovative uses to overcome the limitations of traditional decision-making approaches.

Taking esophageal cancer as an example, early screening and diagnosis are of paramount importance, yet traditional methods have inherent limitations. The advent of AI-based early esophageal cancer imaging screening platforms, which rely on deep learning algorithms to analyze vast amounts of imaging data, has enabled the accurate identification of early lesions with a diagnostic accuracy exceeding 90%. This provides an objective basis for disease assessment in SDM [51–53]. Specifically, these platforms can precisely detect early lesions in endoscopic images and generate intuitive diagnostic reports, offering accurate disease information for SDM [53]. With this information, physicians can more clearly explain the patient’s condition, enhancing the patient’s understanding and acceptance of treatment options and encouraging their active participation in SDM.

Furthermore, a 2023 assessment by Guidozzi N et al. [54], which evaluated 14 studies involving 1,590 patients, revealed that when AI was used for the endoscopic diagnosis of esophageal squamous cell carcinoma, the pooled sensitivity and specificity were 91.2% and 80%, respectively. For the assessment of AI’s ability to diagnose esophageal adenocarcinoma across nine studies involving 478 patients, the pooled sensitivity and specificity were 93.1% and 86.9%, respectively. As an endoscopic adjunct technology, AI contributes to the accurate and early detection of esophageal malignancies, providing robust support for SDM in the diagnosis and treatment of esophageal cancer.

AI can also integrate patients’ clinical data (such as age, pathological type, and genetic test results), treatment efficacy data, and patient preferences to construct personalized decision-making models and offer treatment recommendations to physicians [55]. Based on these recommendations, physicians can engage in in-depth discussions with patients, weigh the pros and cons, and make more rational decisions. In a 2025 study by Hirata A et al. [56], a retrospective analysis was conducted on 70 patients with esophageal squamous cell carcinoma (ESCC) who underwent chemoradiotherapy (CRT) followed by surgery. Radiomic features extracted from pre-treatment diffusion-weighted magnetic resonance imaging (DWI-MRI) images were modeled using AI (based on the AutoGluon automated machine learning library) to predict pathological complete response (pCR), with stratified double cross-validation employed. This AI-based radiological analysis holds promise for contributing to the development of optimal treatment strategies for esophageal cancer and facilitating SDM.

The application of AI in SDM has brought about transformative changes in the diagnosis and treatment of esophageal cancer, improving the quality of medical services and patient satisfaction, with a broad prospect for future applications. For instance, in the case of patients with advanced esophageal cancer, AI models can predict the efficacy and adverse reaction risks of different chemotherapy regimens, targeted therapies, and immunotherapies based on their genetic test results, providing data support for SDM. However, it is important to note that the results of AI models should be interpreted in conjunction with the physician’s professional experience and the patient’s wishes and should not replace the process of physician-patient communication.

Research on multidisciplinary team involvement in SDM

In the treatment of esophageal diseases, collaboration among multidisciplinary teams (MDTs) is of paramount importance. In recent years, numerous studies have focused on the role of multidisciplinary teams in shared decision-making (SDM), providing new directions for optimizing treatment decisions [57].

Esophageal diseases are characterized by complex conditions and a wide range of treatment modalities. A single discipline often finds it challenging to comprehensively evaluate the patient’s condition and formulate the optimal treatment plan. Therefore, it is essential to establish a team composed of doctors from various disciplines, such as thoracic surgery, medical oncology, and radiology, to conduct a thorough assessment of patients [46]. Thoracic surgeons can determine surgical indications, evaluate surgical risks, analyze the advantages and disadvantages of different surgical approaches, and offer surgical recommendations to patients. Medical oncologists can formulate drug treatment plans based on the patient’s condition, predict treatment efficacy and adverse reactions, and introduce relevant drug information to patients. Radiologists can utilize advanced imaging techniques to provide objective evidence for disease diagnosis and assessment and explain the patient’s condition in an intuitive manner [58].

The MDT team should include professional doctors from thoracic surgery, medical oncology, gastroenterology, radiology, and nutrition, among others, to provide comprehensive assessment and treatment recommendations for patients through joint consultations [57]. In the context of SDM, members of the multidisciplinary team engage in in-depth communication with patients and their families. In a retrospective cohort study, 68 patients with early-stage esophageal squamous cell carcinoma (ESCC) from four tertiary referral hospitals in the Netherlands between 2012 and 2017 were included [59]. Doctors from various disciplines provided comprehensive information from their professional perspectives, covering aspects such as the efficacy, safety, cost, and impact on quality of life of different treatment options. After fully considering these opinions, patients participated in the formulation of the treatment plan based on their own circumstances. This study emphasized the crucial role of multidisciplinary teams in the assessment and management before and after endoscopic submucosal dissection (ESD) surgery, including the collaboration among endoscopists, pathologists, and surgeons. This approach helps improve the scientificity and rationality of decision-making, ensuring that the treatment plan is more tailored to the individual needs of patients.

The involvement of multidisciplinary teams in SDM can enhance the quality of treatment decisions for esophageal diseases, provide personalized services, promote communication and trust between doctors and patients, and ultimately achieve the goals of optimizing treatment and improving patients’ quality of life. The specific implementation process is as follows: (1) The MDT team conducts a comprehensive assessment of the patient’s condition, clarifying key information such as disease stage, pathological type, and organ function status. (2) Doctors from each discipline propose treatment recommendations from their professional perspectives, analyzing their efficacy, risks, and applicable conditions. (3) A coordinating doctor summarizes the opinions from multiple disciplines and presents them to patients and their families in an easy-to-understand manner while answering any questions. (4) Doctors and patients jointly determine the final treatment plan, taking into account the patient’s preferences and family support situation.

A retrospective study involving 68 patients with early-stage esophageal squamous cell carcinoma demonstrated that SDM with MDT involvement could increase the scientificity of the treatment plan by 35%, enhance patient decision-making satisfaction by 40%, and reduce the incidence of postoperative complications by 22% [59]. However, the effective operation of an MDT requires the establishment of fixed consultation times, standardized case discussion procedures, and an information support system. Currently, some hospitals in China still lack a well-established MDT collaboration mechanism, which necessitates gradual improvement through policy guidance and resource investment.

Limitations and future research directions

This structured narrative review comprehensively summarizes the application, advantages, challenges and optimization strategies of SDM across all esophageal disorders, and all conclusions are interpreted with full recognition of existing evidence limitations.

Limitations of this study

1. Limitations in Evidence Integration: The existing studies on the application of shared decision-making (SDM) in esophageal diseases are mostly single-center and small-sample designs, lacking multi-center, large-sample randomized controlled trials. Some studies have relatively short follow-up periods (< 1 year), making it difficult to evaluate the long-term effects of SDM. Additionally, there are differences in the implementation methods and evaluation indicators of SDM across different studies, which pose challenges for evidence integration.

2. Limitations in the Implementation Framework: The three-dimensional framework of “disease classification - evidence hierarchy - patient preference” constructed in this paper is still in the theoretical construction stage and requires validation and optimization through clinical practice. The assessment of patient preference within the framework does not take into account potential influencing factors such as psychological factors and family support, which may affect the pertinence of decision-making recommendations.

3. Limitations in Geographical Applicability: The evidence in this study is mainly derived from relevant domestic and international research, without fully considering the impact of differences in medical resource distribution and healthcare insurance policies across different regions on the implementation of SDM. Its applicability in primary hospitals and resource-constrained areas needs further exploration.

In addition, the existing evidence supporting the clinical benefits of SDM has several common methodological defects. Most relevant primary studies are retrospective single-center researches, which may bring potential selection bias. Publication bias is also prevalent in this field, as positive research results are more likely to be published while negative or neutral outcomes are often neglected. Moreover, the specific implementation protocols, assessment tools and intervention modes of SDM differ greatly across studies, leading to obvious methodological heterogeneity. In addition, long-term follow-up data exceeding 2 years are insufficient, which limits the generalizability of the current research conclusions.

Future research directions

1. Conduct High-Quality Clinical Research: Design multi-center, large-sample randomized controlled trials to compare the clinical effects of SDM and traditional decision-making models in different esophageal diseases. Adopt an evaluation system that combines objective outcome indicators (such as survival rate, complication incidence rate, and medical costs) with subjective indicators (such as decision-making satisfaction and quality of life). Conduct long-term follow-up studies to clarify the impact of SDM on patients’ long-term prognosis.

2. Develop Disease-Specific Decision-Aid Tools: Based on the three-dimensional framework constructed in this paper, develop SDM decision-aid tools for different esophageal diseases, such as treatment option selection scales for early-stage esophageal cancer and decision trees for long-term management of gastroesophageal reflux disease (GERD). Combine artificial intelligence technology to develop intelligent decision-aid systems that enable automatic analysis of patient data and personalized recommendation of treatment plans.

3. Explore Intervention Strategies for Obstacles to SDM Implementation: Develop targeted intervention measures to address obstacles such as the lag in doctors’ concept transformation and differences in patients’ participation abilities, such as SDM training courses for doctors and health literacy enhancement programs for patients. Evaluate the effectiveness and feasibility of different intervention measures to provide support for the promotion and application of SDM.

4. Improve the MDT Collaboration Mechanism: Conduct research on the implementation path of multidisciplinary team (MDT) involvement in SDM, clarifying key elements such as the composition, operational procedures, and communication methods of MDT. Evaluate the cost-effectiveness ratio of the MDT-SDM model to provide a basis for hospital administrators in policy formulation.

Conclusion

As this structured narrative review demonstrates, Shared decision-making (SDM), as a “patient-centered” medical decision-making model, shows promising clinical potential rather than definitive universal efficacy in the treatment of esophageal diseas esespecially in surgical decision-making of esophageal cancer.Current observational evidence preliminarily indicates that SDM may improve patient decision satisfaction, treatment adherence and doctor-patient communication, yet these benefits require verification via large prospective trials, and improve the selection of treatment plans. Based on the existing evidence, the application of SDM in esophageal diseases can notably increase patient decision-making satisfaction (moderate-quality evidence), improve treatment adherence (low- to moderate-quality evidence), and enhance the doctor-patient relationship (moderate-quality evidence). However, the specific effects vary depending on the disease type, patient characteristics, and the healthcare environment.

Nevertheless, the application of this model in the field of esophageal disease treatment still faces challenges such as the lag in doctors’ concept transformation, differences in patients’ participation abilities, and limitations in time and resources. The widespread adoption of SDM in esophageal diseases encounters real-world challenges, including the slow transformation of doctors’ attitudes, variations in patients’ participation capabilities, and constraints on medical resources. Its promotion requires collaborative efforts from multiple aspects.

In recent years, significant progress has been made in research on SDM in the field of esophageal diseases. The application of SDM in neoadjuvant treatment decisions provides patients with more treatment options. Artificial intelligence-assisted SDM enhances patients’ decision-making abilities through decision support tools. The involvement of multidisciplinary teams in SDM integrates the advantages of various disciplines, offering patients more comprehensive diagnosis and treatment recommendations. The three-dimensional SDM implementation framework of “disease classification - evidence hierarchy - patient preference” constructed in this paper provides a standardized path for the application of SDM in different types of esophageal diseases, demonstrating strong clinical practicality.

In the future, it is necessary to promote the widespread application of SDM in the clinical practice of esophageal diseases through measures such as strengthening doctor training, improving patients’ health literacy, enhancing policy and resource support, developing and applying decision-aid tools, and building multidisciplinary teams. Ultimately, the goal of providing patients with higher-quality and personalized medical services can be achieved.Notably, most supporting evidence originates from single-center, retrospective and heterogeneous studies; multicenter, long-term prospective researches focusing on distinct esophageal subtypes are urgently needed to validate the stable clinical benefits of SDM.

Authors’ contributions

YY was involved in drafting the manuscript. JZ, XL, MY CZand KL were involved in acquisition of data. CS designed and revised the manuscript.

Funding

This paper was supported by the Natural Science Foundation of Sichuan Province (No.2024NSFSC1924) (to Cheng SHEN).

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

Approval of the research protocol by an Institutional Reviewer Board: N/A.

Informed Consent: N/A.

Registry and the Registration No. of the study/trial: N/A.

Animal Studies: N/A.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.