Systematic review of multidisciplinary team strategies and novel research in rare and complex clinical cases

Abstract

BACKGROUND

Rare and complex clinical cases often lack standardized management protocols, posing significant diagnostic and therapeutic challenges. Multidisciplinary team (MDT) collaboration provides holistic perspectives by integrating surgical, medical, radiological, pathological, and psychosocial expertise. Concurrently, innovative research - including precision medicine, artificial intelligence-driven diagnostics, and novel therapeutics - is bridging the gap between theory and practice. Synthesizing current evidence on MDT-driven approaches and innovative interventions is essential to improve patient outcomes, establish standardized frameworks, and advance global clinical medicine.

AIM

To systematically review MDT roles and innovative research in managing rare and complex clinical cases.

METHODS

A systematic search of PubMed and Cochrane Library (2013-2025) was conducted. Eligible studies included case reports, case series, systematic reviews, and clinical trials involving rare or complex cases with MDT involvement. Non-peer-reviewed sources and anecdotal reports were excluded. Data extraction focused on MDT composition, decision-making processes, innovative interventions, and patient outcomes. Study quality was assessed using PRISMA guidelines.

RESULTS

Evidence demonstrates that MDTs enhance diagnostic accuracy, optimize treatment planning, and improve survival in oncology, cardiology, and neurology. Rare congenital anomalies and complex autoimmune disorders particularly benefit from cross-specialty collaboration. Innovative research achievements include genetic profiling for precision therapies, machine learning models predicting rare disease progression, and novel therapeutics such as immunotherapy and regenerative medicine. Case-based evidence highlights rare sarcomas, congenital heart defects, and atypical autoimmune syndromes, where early MDT involvement and integration of research findings yielded improved patient quality of life and clinical outcomes.

CONCLUSION

MDT-driven strategies, combined with innovative research, are transforming rare case management, advancing clinical medicine, and contributing to improved global health outcomes.

Key Words: Rare clinical cases; Complex case management; Multidisciplinary team; Innovative clinical research; Translational medicine

Core Tip: Rare and complex clinical cases require multidisciplinary team collaboration and integration of innovative research to achieve optimal outcomes. This systematic review highlights how multidisciplinary team-driven strategies, precision medicine, artificial intelligence, and novel therapeutics are transforming case management, improving patient survival and quality of life, and advancing global clinical practice. Though long-term outcome evidence remains limited, process-level benefits and integration of innovative technologies establish multidisciplinary teams as central to modern complex care. Strengthening the evidence base through standardized, high-quality research is essential to optimize implementation and improve patient outcomes.

INTRODUCTION

Rare and complex clinical cases represent a distinct and challenging category within modern clinical medicine. Rare diseases are commonly defined as conditions affecting fewer than 1 in 2000 individuals, yet collectively they impact an estimated 300-400 million people worldwide, underscoring their global public health relevance[1]. Complex clinical cases, which often involve multimorbidity, atypical presentations, diagnostic uncertainty, or highly individualized therapeutic needs, similarly pose significant diagnostic and management challenges. These cases are frequently associated with delayed diagnosis, fragmented care pathways, and limited evidence-based guidance, largely due to their low prevalence, phenotypic heterogeneity, and exclusion from large clinical trials[1]. Consequently, conventional single-specialty approaches are often insufficient to address the multifaceted diagnostic and therapeutic demands of such cases. Historically, management relied on isolated specialty expertise, which often proved inadequate for multifaceted presentations, highlighting the need for integrated care models.

In this context, multidisciplinary team (MDT) collaboration has emerged as a rational and increasingly essential model of care. MDTs bring together expertise from surgical, medical, radiological, pathological, genetic, and psychosocial disciplines, enabling comprehensive case assessment and integrated clinical decision-making[2]. The rationale for MDT-based care lies in its capacity to synthesize diverse clinical data, reduce diagnostic uncertainty, and align complex therapeutic strategies within a coordinated framework. In oncology, MDT involvement has consistently been associated with improved diagnostic accuracy, optimized treatment selection, and enhanced survival outcomes[3,4]. Importantly, the applicability of MDT models extends beyond cancer care. Evidence from studies involving multimorbid hospitalized patients, complex cardiovascular disease, and neurological disorders demonstrates that structured MDT approaches reduce variability in care delivery, facilitate individualized management plans, and improve long-term functional outcomes[5-7]. These findings highlight the critical role of MDTs in managing rare congenital anomalies, atypical autoimmune syndromes, and other complex clinical scenarios where isolated specialty-driven care is inadequate[8]. The growing adoption of MDTs across diverse specialties reflects a broader shift toward patient-centered, coordinated care frameworks in modern healthcare systems[2,5].

Concurrently, innovative research paradigms are transforming the clinical management of rare and complex cases. Precision medicine, driven by advances in genetic and molecular profiling, enables targeted therapeutic interventions tailored to disease-specific biological mechanisms[8]. Artificial intelligence (AI) and machine learning technologies are increasingly integrated into clinical workflows to support diagnostic interpretation, risk stratification, and prediction of disease trajectories in complex clinical settings[9,10]. Furthermore, emerging therapeutic modalities-including immunotherapy and regenerative medicine-are progressively bridging the gap between experimental research and clinical application, offering novel treatment options for patients with conditions previously lacking effective therapies[11]. Together, these innovations complement MDT strategies, creating opportunities for highly individualized and evidence-informed care[8,11].

Despite these advances, significant challenges persist. Effective MDT implementation is frequently limited by communication gaps, resource constraints, and variability in institutional infrastructure and support[2]. Additionally, the translation of innovative research into routine clinical practice requires rigorous validation, ethical oversight, and equitable access across diverse healthcare systems[8,11]. Addressing these challenges is essential for establishing standardized, evidence-based frameworks that can guide clinicians globally in the management of rare and complex clinical cases[5].

Against this background, this systematic review aims to synthesize current evidence on MDT strategies and innovative research interventions in rare and complex clinical cases. By integrating findings from case reports, clinical trials, and systematic reviews, this review seeks to elucidate how collaborative care models and translational research are reshaping clinical decision-making, improving patient outcomes, and advancing contemporary clinical practice.

MATERIALS AND METHODS

Study design and reporting framework

This systematic review was conducted according to the PRISMA 2020 guidelines. The review protocol was not registered in PROSPERO or any other public database; however, all methodological steps were predefined to ensure transparency, reproducibility, and rigor in evaluating MDT strategies and novel research in rare and complex clinical cases.

A structured methodology was pre-specified, including search strategy, eligibility criteria, screening procedures, data extraction, and quality appraisal. The scope of the review included case reports, case series, systematic reviews, and clinical trials focusing on rare and complex clinical cases with MDT involvement and innovative research applications.

No meta-analysis of pooled reports was performed due to heterogeneity in reference standards, patient populations, and reporting metrics. Instead, study-level accuracy values and clinical outcomes were extracted and synthesized narratively. Risk of bias was assessed using the QUADAS-2 tool. Grey literature sources and preprints were excluded, and only peer-reviewed publications were considered, which may have introduced publication bias.

Search strategy

A comprehensive literature search was conducted using PubMed and the Cochrane Library, both freely accessible databases providing high-quality biomedical and clinical literature. The search covered studies published from January 2013 to December 2025. This timeframe was deliberately selected to capture evidence reflecting contemporary MDT models and current standards of clinical practice[12].

Subscription-based databases such as EMBASE, Scopus, and Web of Science were not searched due to institutional access limitations. To mitigate this limitation, a broad and highly sensitive PubMed search strategy was employed, supplemented by searching the Cochrane Library and manual screening of reference lists from included studies.

From 2013 onward, MDT care evolved from informal interspecialty consultations to structured, protocol-driven clinical frameworks, particularly in oncology, rare diseases, and complex multisystem disorders[2,3]. This period also corresponds to the widespread clinical adoption of genomic diagnostics, precision medicine approaches, and the emergence of AI-assisted decision-making, which are central to the objectives of this review[13-15].

Earlier studies were excluded because they frequently predated standardized MDT workflows, molecular disease classification, and modern diagnostic technologies, thereby limiting their applicability to current clinical practice[16]. Restricting the search period enhanced methodological consistency, reduced clinical heterogeneity, and ensured that included evidence was clinically relevant, translational, and aligned with contemporary MDT-driven care paradigms[17].

Free-text terms were searched in the title and abstract fields using PubMed field tags ([tiab]) and were combined with relevant Medical Subject Headings to ensure comprehensive retrieval. Thus, PubMed strategy combined Medical Subject Headings and free-text terms related to multidisciplinary and team-based care (including tumor boards and integrated care models) with terms describing rare or complex clinical conditions. To minimize under-inclusion, multiple synonymous and functionally equivalent descriptors of multidisciplinary care were incorporated. The Cochrane Library was searched using analogous keyword strategies. This search approach is consistent with PRISMA recommendations and systematic review best practices when reviewing heterogeneous and emerging fields. Searches were restricted to human studies published in English. The complete electronic search strategy for each database is provided in Table 1.

Table 1 Electronic database search strategy.

Database	Search terms	Limits applied
PubMed	(“Patient Care Team”[Mesh] OR “Interdisciplinary Communication”[Mesh] OR “Delivery of Health Care, Integrated”[Mesh] OR “Clinical Decision-Making”[Mesh] OR multidisciplinary[tiab] OR “multidisciplinary team”[tiab] OR MDT[tiab] OR interdisciplinary[tiab] OR interprofessional[tiab] OR “team-based care”[tiab] OR “integrated care”[tiab] OR “collaborative care”[tiab] OR “tumor board”[tiab] OR “tumour board”[tiab] OR “molecular tumor board”[tiab] OR “case conference”[tiab] OR “expert panel”[tiab] OR “precision medicine board”[tiab] OR “genomic board”[tiab]) AND (“Rare Diseases”[Mesh] OR “Neoplasms”[Mesh] OR “Cardiovascular Diseases”[Mesh] OR “Nervous System Diseases”[Mesh] OR “Congenital Abnormalities”[Mesh] OR “Autoimmune Diseases”[Mesh] OR rare disease*[tiab] OR complex condition*[tiab] OR oncology[tiab] OR cancer*[tiab] OR cardiology[tiab] OR neurology[tiab] OR congenital[tiab] OR autoimmune[tiab]) AND (“Precision Medicine”[Mesh] OR “Artificial Intelligence”[Mesh] OR “Genomics”[Mesh] OR “High-Throughput Nucleotide Sequencing”[Mesh] OR “Decision Support Systems, Clinical”[Mesh] OR precision medicine[tiab] OR genomic*[tiab] OR AI[tiab] OR “artificial intelligence”[tiab] OR “machine learning”[tiab] OR “clinical decision support”[tiab])	Humans; English; 2013-2025
Cochrane Library	(Multidisciplinary OR interdisciplinary OR interprofessional OR “team-based care” OR “integrated care” OR “collaborative care” OR “tumor board” OR “tumour board” OR “case conference” OR “expert panel”) AND (rare OR complex OR oncology OR cancer OR cardiology OR neurology OR congenital OR autoimmune)	2013-2025

MDT: Multidisciplinary team.

Inclusion and exclusion criteria

Inclusion criteria: Population: Patients with rare or complex clinical conditions (oncology, cardiology, neurology, congenital anomalies, autoimmune syndromes). Intervention/exposure: Involvement of MDT strategies (medical, surgical, radiological, pathological, psychosocial). Comparator: Standard or single-specialty care, when available. Outcomes: Diagnostic accuracy, treatment planning, survival, quality of life, or integration of innovative research (precision medicine, AI-driven diagnostics, novel therapeutics). Study types: Case reports, case series, systematic reviews, and clinical trials.

Exclusion criteria: Non-peer-reviewed sources, anecdotal reports, editorials, conference abstracts without full data, grey literature, and preprints. Studies not involving MDTs or innovative interventions.

Data extraction and synthesis

Extracted data included MDT composition, clinical decision pathways, innovative technologies used (genomics, AI), study design, primary outcomes (diagnostic yield, treatment effectiveness), and limitations. Quality assessment aligned with PRISMA guidelines and was performed using QUADAS-2.

RESULTS

Study selection

Database searching from January 2013 to December 2025 yielded a total of 1399 citations. After the removal of 12 duplicates, 1387 records underwent title and abstract screening, of which 1338 were excluded for not meeting the MDT or complex condition criteria. Forty-nine full-text articles were assessed for eligibility, and 17 were excluded based on predefined criteria (e.g., lack of innovative interventions or grey literature). Consequently, 32 studies were included in the qualitative synthesis. The study selection process is illustrated in the PRISMA 2020 flow diagram (Figure 1).

Figure 1 PRISMA flow diagram. MDT: Multidisciplinary team.

Risk of bias assessment

Risk of bias was assessed using an adapted QUADAS-2 framework (Table 2). Across the included studies, concerns related to risk of bias were primarily associated with retrospective study designs, limited reporting of reference standards, and absence of comparator arms. Several studies were rated as having unclear risk in one or more QUADAS-2 domains due to insufficient methodological detail. No studies were excluded on the basis of quality assessment, and all were retained for qualitative synthesis.

Table 2 QUADAS-2 summary table.

Domain	Low risk	Unclear risk	High risk
Patient selection	21-24	6-8	0
MDT process/index test	24-28	3-4	0
Reference standard	18-20	9-12	0
Flow and timing	20-24	7-8	0

MDT: Multidisciplinary team.

Study characteristics

The included studies were published from January 2013 to December 2025 and were predominantly conducted in oncology settings, with additional representation from cardiology, neurology, and autoimmune disease management[18-22]. Study designs were heterogeneous and included case reports, case series, observational cohort studies, qualitative analyses, consensus statements, and clinical trial protocols[18-19,23]. Studies were conducted across multiple geographic regions, including Europe, North America, and Latin America, reflecting international adoption of MDT-based care models[19,20,22,24,25].

MDT models

All included studies explicitly described the involvement of MDTs in clinical decision-making. MDT composition commonly included medical specialists alongside surgical, radiological, and pathological disciplines[18-20]. Several studies reported expanded MDT membership, incorporating molecular pathologists, geneticists, nurses, bioinformaticians, and allied health professionals, particularly in the context of molecular tumor boards and precision medicine initiatives[19,22,24,26,27]. MDT formats varied and included traditional in-person meetings, molecular tumor boards, and virtual or network-based MDT platforms, reflecting evolving models of multidisciplinary care delivery across diverse healthcare systems[19-22].

Integration of innovation

Most included studies reported the use of advanced diagnostic or decision-support technologies within MDT workflows, particularly in oncology and other high-complexity clinical settings[19,24,26,27]. Frequently reported innovations included next-generation sequencing, molecular profiling, and precision medicine approaches, most commonly discussed within molecular tumor board frameworks[19,24,26]. In several studies, MDT review following integration of molecular or genomic data was associated with diagnostic reclassification or modification of treatment strategies, including escalation to targeted therapies or de-escalation of ineffective interventions[19,23,27]. Key characteristics of the included studies, including clinical domains, MDT composition, models of care, innovations, and reported outcomes, are summarized in Table 3[27-48].

Table 3 Characteristics and outcomes of included studies.

Domain	Summary	Representative references
Clinical area	Studies predominantly addressed oncology, with additional representation from cardiology, neurology, and autoimmune diseases. Rare cancers, congenital cardiovascular disease, complex neurological disorders, and atypical autoimmune syndromes were commonly reported	Oncology:[18,19,22,26-39,45,46]; cardiology/congenital heart disease:[21,40,41]; neurology:[42,47]; autoimmune/complex disease contexts:[43,48]
MDT composition	MDTs typically included physicians and surgeons, with regular involvement of radiologists and pathologists. Expanded MDTs incorporated molecular pathologists, geneticists, nurses, allied health professionals, and bioinformaticians in complex cases	[18,19,23,26-28,30,33-38,42,45,46]
MDT model	MDT formats included traditional tumor boards, molecular tumor boards, interdisciplinary case conferences, and virtual or network-based MDTs, particularly for rare or geographically dispersed cases	Traditional MDTs:[19,22,29,30,36,39,42]; molecular tumor boards:[18,23,26-28,31,34,38]; virtual/network MDTs:[23,36-37,44]
Innovation	Studies reported integration of genomics, precision medicine, high-throughput sequencing, and artificial intelligence-assisted clinical decision support within MDT workflows, particularly in oncology and rare disease care	Genomics/NGS:[18,26-28,31-35,38]; precision medicine:[18,26-28,44]; AI/ML decision support:[29,37]
Outcomes	MDT involvement was associated with improved diagnostic accuracy, treatment modification, and optimized care pathways. Evidence for survival and quality-of-life benefits was limited and heterogeneous, with outcomes often reported as intermediate or process-level measures	Diagnostic/treatment modification:[18,23,26-28,30,34,38]; care pathway optimization/process outcomes:[21,23,38,42,44]; limited survival/quality-of-life data:[19,22,30,39]

MDT: Multidisciplinary team; NGS: Next-generation sequencing; AI: Artificial intelligence; ML: Machine learning.

DISCUSSION

Summary of main findings and strength of evidence

This systematic review synthesized evidence from 32 peer-reviewed studies published from 2013 to 2025 evaluating MDT-based approaches in the management of rare and complex clinical conditions. Across clinical domains-predominantly oncology, with additional representation from cardiology, neurology, and autoimmune diseases-the findings consistently indicate that MDT involvement is associated with improvements in diagnostic clarification, treatment planning, and integration of innovative diagnostic and therapeutic technologies[18-22,24,25]. These results highlight that in the modern era of precision medicine, MDTs act as essential vehicles for translating complex genomic and proteomic data into actionable clinical pathways.

The most consistent evidence across included studies related to process-level outcomes, particularly diagnostic reclassification and modification of treatment strategies following MDT review. As demonstrated in several oncology-focused and molecular tumor board studies, multidisciplinary discussion frequently resulted in changes to diagnosis or management, including refinement of disease classification and selection of targeted therapies[18-20,24,26,27]. Notably, recent evidence in urological oncology and neuro-genetics suggests that these improvements are increasingly driven by the formal inclusion of molecular biologists and geneticists within the core MDT structure to interpret high-complexity data. These effects were observed across different MDT formats, including traditional in-person meetings, molecular tumor boards, and virtual or network-based MDT models, suggesting that the observed benefits are not restricted to a single organizational structure[19-21].

Evidence supporting the integration of innovative technologies within MDT workflows was moderate and coherent. Studies describing next-generation sequencing, molecular profiling, and precision medicine approaches consistently reported that MDTs facilitated interpretation of complex genomic data and informed clinical decision-making[24,26,27]. Specifically, the rise of prostate-specific membrane antigen-targeted theranostics and homologous recombination repair gene testing underscores a fundamental shift toward “molecular MDTs” as the standard of care for complex cases. However, the methodological quality of these studies, as assessed using an adapted QUADAS-2 framework, was variable, with several studies demonstrating unclear risk of bias due to retrospective design and limited reporting of reference standards or comparators.

In contrast, evidence for hard clinical endpoints, such as overall survival and quality of life, was limited. Few studies reported long-term follow-up or patient-reported outcomes, and those that did primarily relied on surrogate or intermediate endpoints rather than direct survival analyses[18,20,22,24]. Consequently, the strength of evidence supporting survival or quality-of-life benefits remains low, underscoring an important gap in the current literature (Table 4)[18-22,26,27,45-49].

Table 4 Evidence synthesis of included studies[18-22,26,27,45-49].

Dimensions	Findings
Clinical domains	Oncology (dominant), cardiology, autoimmune disease
MDT composition	Oncologists, surgeons, radiologists, pathologists, geneticists, cardiologists, nurses, bioinformaticians
MDT format	In-person MDTs, molecular tumor boards, virtual/tele-MDTs
Innovation integrated	NGS, molecular profiling, AI/ML decision tools, liquid biopsy, precision therapeutics
Primary MDT function	Diagnostic clarification, treatment selection, escalation/de-escalation decisions
Outcomes reported	Diagnostic reclassification, altered management, feasibility of innovation integration
Survival/quality-of-life data	Limited direct reporting; mostly surrogate and process outcomes
Study design heterogeneity	Case reports → cohorts → qualitative and consensus studies
Geographic distribution	Europe, North America, Latin America

MDT: Multidisciplinary team; NGS: Next-generation sequencing; AI: Artificial intelligence; ML: Machine learning.

Relevance to key stakeholders

For clinicians, these findings support the integration of MDTs into the routine management of patients with diagnostically or therapeutically complex conditions. MDT-based approaches enable comprehensive clinical evaluation, promote shared decision-making, and facilitate the application of precision medicine within real-world care settings[18-21,24,26]. Contemporary “alliance-based” models further suggest that multidisciplinary collaboration should ideally begin at the primary care level to shorten the “diagnostic odyssey” for rare diseases.

For patients, MDT care represents a structured and patient-centered model that incorporates multiple expert perspectives, with the potential to reduce diagnostic uncertainty and optimize individualized treatment strategies[18,19,22,24]. Although patient-reported outcomes were inconsistently assessed across included studies, improved coordination of care and clearer treatment pathways were frequently reported, which may translate into better patient experience and satisfaction[19,20,22].

For healthcare systems and policy makers, MDTs function as enabling platforms for the adoption of advanced diagnostics and digital health innovations. Our findings emphasize that MDTs are no longer just advisory boards but are critical infrastructure for the equitable implementation of genomics-informed care. The emergence of virtual and tele-MDT models identified in this review highlights opportunities to improve access to specialist expertise, particularly for geographically remote or resource-limited settings, while supporting equitable implementation of precision medicine and genomics-informed care[19-21,24].

Limitations

Study-level limitations: Several limitations at the study level should be acknowledged. Many included studies were observational, retrospective, or case-based, which introduces potential selection bias and limits causal inference. The descriptive nature of several recent consensus and pathway guidelines, while clinically significant, often lacks the rigorous control of randomized trials. Outcome reporting was heterogeneous, and methodological transparency varied across studies. As reflected in the QUADAS-2 assessment, unclear risk of bias was frequently related to participant selection and incomplete reporting of reference standards or comparators.

Review-level limitations: At the review level, although comprehensive database searching and predefined inclusion criteria were applied, incomplete retrieval of relevant studies cannot be excluded. Restriction to English-language publications may have introduced language bias, and publication bias is possible given the predominance of feasibility-focused and positive reports. Additionally, heterogeneity in study design and outcome measures from 2013 to 2025 precluded quantitative meta-analysis, limiting estimation of pooled effects.

Interpretation in the context of existing evidence

The findings of this review are consistent with prior reports emphasizing the value of MDTs in oncology and other high-complexity clinical settings. However, this review extends existing literature by systematically synthesizing evidence across multiple specialties and highlighting the evolving role of MDTs as platforms for integrating genomic and computational innovations into clinical care. Our synthesis uniquely illustrates that the MDT model is expanding beyond the “tumor board” into neurology and cardiology as a direct response to the increasing complexity of molecular diagnostics and AI-driven care.

Implications for future research

Future studies should prioritize prospective, longitudinal designs to assess the impact of MDTs on survival, quality of life, and healthcare utilization. There is a specific need for “implementation science” research to determine how these resource-intensive molecular MDT pathways can be efficiently scaled. Standardized reporting of MDT structure, composition, and outcomes would enhance comparability across studies. Greater emphasis on patient-reported outcomes, economic evaluations, and equity of access is also needed. Rigorous evaluation of emerging technologies, including AI and telemedicine platforms, within MDT workflows will be essential to ensure effective and equitable implementation.

CONCLUSION

This systematic review demonstrates that MDT-based care is consistently associated with improvements in diagnostic and decision-making processes for patients with rare and complex clinical conditions. While evidence for long-term clinical outcomes remains limited, the observed process-level benefits and successful integration of innovative technologies support MDTs as a core component of contemporary complex care. Strengthening the evidence base through standardized, high-quality research will be critical to optimizing MDT implementation and patient outcomes.