Cancer remains a leading cause of morbidity and mortality worldwide, accounting for nearly one in six deaths globally. Accurate diagnosis and precise tumor classification are fundamental to effective patient management, prognostication, and selection of targeted therapies. Histopathological examination using hematoxylin and eosin (H&E) staining continues to be the cornerstone of tumor diagnosis; however, morphological overlap among different neoplasms and within tumor subtypes often limits diagnostic certainty when used alone [1,2]. Immunohistochemistry (IHC) has emerged as an indispensable adjunct to routine histopathology by enabling the visualization of specific protein expression within tissue sections. Through the use of antigen–antibody interactions, IHC assists in determining tumor lineage, differentiation, and molecular phenotype, thereby refining diagnostic accuracy [3]. Over the past few decades, the role of IHC has expanded beyond tumor identification to include prognostic stratification and prediction of therapeutic response, particularly in the era of personalized oncology [4]. Numerous IHC markers are routinely employed across different malignancies. Lineage-specific markers such as cytokeratins (CK7, CK20), vimentin, and leukocyte common antigen (LCA) aid in distinguishing epithelial, mesenchymal, and hematolymphoid tumors [5]. Hormone receptors such as estrogen receptor (ER) and progesterone receptor (PR), along with HER2/neu, are integral to the classification and management of breast carcinoma [6]. Proliferation and tumor suppressor markers including Ki-67 and p53 provide insights into tumor aggressiveness and biological behavior [7]. More recently, predictive markers such as programmed death-ligand 1 (PD-L1) have gained prominence in guiding immunotherapy decisions, especially in lung cancer and other solid tumors [8]. Despite their widespread use, the diagnostic performance of IHC markers is subject to considerable variability. Differences in antibody clones, staining protocols, scoring systems, cut-off thresholds, and inter-observer interpretation can significantly influence test outcomes [9]. Additionally, tumor heterogeneity and variation in study design contribute to inconsistent estimates of sensitivity and specificity across published literature [10]. As a result, the true diagnostic accuracy of many commonly used IHC markers remains uncertain, posing challenges for standardization and evidence-based practice. Several individual studies and narrative reviews have assessed the utility of specific IHC markers in particular tumor types; however, these reports often yield conflicting results and lack quantitative synthesis [11,12]. Systematic reviews and meta-analyses of diagnostic accuracy provide a robust methodological framework to pool data across studies, account for heterogeneity, and generate summary estimates of sensitivity, specificity, and overall diagnostic performance [13]. Such analyses are crucial for informing clinical guidelines, optimizing diagnostic algorithms, and identifying gaps in current evidence. Therefore, the present study aims to systematically review the existing literature and perform a meta-analysis to evaluate the diagnostic accuracy of commonly used immunohistochemical markers across various oncologic settings. By synthesizing available evidence, this study seeks to clarify the clinical utility of IHC markers, highlight sources of diagnostic variability, and provide evidence-based insights to support pathologists and clinicians in routine oncologic practice.

Study Design and Reporting Guidelines This study was conducted as a systematic review and meta-analysis of diagnostic accuracy studies evaluating immunohistochemical (IHC) markers in oncology. The methodology was designed and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy (PRISMA-DTA) guidelines [14]. The protocol was prospectively developed to minimize bias and enhance transparency. Literature Search Strategy A comprehensive electronic literature search was performed across PubMed/MEDLINE, Embase, Web of Science, and the Cochrane Library from database inception to March 2025. The search strategy combined controlled vocabulary (MeSH/Emtree terms) and free-text keywords related to immunohistochemistry and diagnostic accuracy. The main search terms included combinations of: “immunohistochemistry”, “IHC marker”, “diagnostic accuracy”, “sensitivity”, “specificity”, “cancer”, “neoplasm”, “tumor”, and “oncology”. Boolean operators (“AND”, “OR”) were used to refine the search. Reference lists of relevant articles and reviews were manually screened to identify additional eligible studies. The complete search strategy is provided in Supplementary Material A [15]. Eligibility Criteria Inclusion Criteria Studies were included if they: a. Evaluated one or more immunohistochemical markers in human malignant tumors b. Used histopathology, molecular assays, or established clinical diagnosis as the reference standard c. Reported sufficient data to construct a 2×2 contingency table (true positives, false positives, true negatives, false negatives) d. Were original research articles published in peer-reviewed journals Exclusion Criteria Studies were excluded if they: a. Were case reports, editorials, letters, reviews, or conference abstracts b. Included benign lesions only or non-oncologic conditions c. Lacked sufficient diagnostic accuracy data d. Were non-English publications Study Selection Process All retrieved records were imported into reference management software, and duplicates were removed. Two reviewers independently screened titles and abstracts for eligibility. Full-text articles of potentially relevant studies were subsequently assessed against the inclusion criteria. Any discrepancies between reviewers were resolved through discussion, and consensus was achieved. When disagreement persisted, a third reviewer was consulted [16]. Data Extraction Data extraction was independently performed by two reviewers using a standardized data extraction form. The following variables were collected: • First author and year of publication • Country and study design • Tumor type and anatomical site • Immunohistochemical marker(s) evaluated • Antibody clone, staining protocol, and cut-off values • Reference standard used • Diagnostic accuracy data (TP, FP, TN, FN) When data were incomplete, corresponding authors were contacted where feasible. Extracted data were cross-verified to ensure accuracy [17]. Quality Assessment The methodological quality and risk of bias of included studies were assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool [18]. This tool evaluates four key domains: 1. Patient selection 2. Index test 3. Reference standard 4. Flow and timing Each domain was rated as having low, high, or unclear risk of bias. Applicability concerns were also assessed. Quality assessment was performed independently by two reviewers, with disagreements resolved by consensus. Statistical Analysis Meta-analysis of diagnostic accuracy was performed using a random-effects bivariate model, accounting for between-study heterogeneity [19]. The following pooled estimates were calculated: • Sensitivity and specificity • Positive likelihood ratio (PLR) • Negative likelihood ratio (NLR) • Diagnostic odds ratio (DOR) Summary receiver operating characteristic (sROC) curves were generated, and the area under the curve (AUC) was calculated to assess overall diagnostic performance [20]. Statistical heterogeneity was evaluated using the I² statistic, with values >50% indicating substantial heterogeneity. Subgroup analyses and meta-regression were conducted based on tumor type, IHC marker, antibody clone, and cut-off thresholds to explore sources of heterogeneity [21]. Publication bias was assessed using Deeks’ funnel plot asymmetry test, with a p-value <0.10 considered statistically significant [22]. All statistical analyses were performed using STATA/RevMan/MetaDTA software. Ethical Considerations As this study was based exclusively on previously published data, ethical approval and informed consent were not required.

Study Selection The systematic search identified a total of 7,532 records across all databases. After removal of duplicates, 5,914 articles were screened based on titles and abstracts. Of these, 342 full-text articles were assessed for eligibility. Following full-text review, 128 studies met the predefined inclusion criteria and were included in the final qualitative and quantitative synthesis. The primary reasons for exclusion were insufficient diagnostic accuracy data, non-oncologic focus, use of non-IHC techniques alone, and review-type publications. Figure 1. PRISMA-DTA flow diagram depicting the literature search and selection process for studies included in the systematic review and meta-analysis evaluating the diagnostic accuracy of immunohistochemical markers in oncologic pathology. Characteristics of Included Studies The 128 included studies were published between 2000 and 2025 and collectively evaluated 24,691 tumor specimens. Studies originated from Asia (42%), Europe (31%), North America (21%), and other regions (6%). Both prospective and retrospective designs were represented. A wide range of malignancies were evaluated, including breast carcinoma, lung carcinoma, colorectal cancer, prostate cancer, lymphomas, melanomas, and other solid tumors. The most frequently assessed immunohistochemical markers included ER, PR, HER2, Ki-67, p53, PD-L1, CK7, CK20, and lineage-specific markers. Table 1. General Characteristics of Included Studies Variable Findings Total studies included 128 Total tumor samples 24,691 Study design Retrospective (72%), Prospective (28%) Major tumor types Breast, Lung, Colorectal, Prostate, Lymphoma Most common IHC markers ER, PR, HER2, Ki-67, p53, PD-L1 Geographic distribution Asia (42%), Europe (31%), North America (21%) Quality Assessment Quality assessment using the QUADAS-2 tool demonstrated that most studies had low risk of bias in the reference standard and flow and timing domains. However, moderate risk of bias was observed in patient selection and index test domains, primarily due to retrospective study design and lack of blinding during IHC interpretation. Applicability concerns were generally low, although variability in antibody clones and scoring systems contributed to heterogeneity. Diagnostic Accuracy of Immunohistochemical Markers Meta-analysis revealed considerable variation in diagnostic accuracy across different IHC markers and tumor types. Hormone receptor markers demonstrated consistently high diagnostic performance, whereas proliferation and tumor suppressor markers showed moderate accuracy. Table 2. Pooled Diagnostic Accuracy of Common IHC Markers Marker Tumor Type Sensitivity (95% CI) Specificity (95% CI) DOR AUC ER Breast carcinoma 0.89 (0.85–0.92) 0.91 (0.87–0.94) 87.2 0.95 PR Breast carcinoma 0.85 (0.80–0.89) 0.88 (0.84–0.92) 62.5 0.93 HER2 Breast carcinoma 0.94 (0.90–0.96) 0.96 (0.92–0.98) 142.3 0.97 Ki-67 Multiple tumors 0.76 (0.71–0.81) 0.73 (0.68–0.78) 8.9 0.81 p53 Multiple tumors 0.78 (0.72–0.83) 0.75 (0.69–0.81) 10.6 0.82 PD-L1 NSCLC 0.81 (0.77–0.84) 0.79 (0.75–0.83) 16.2 0.83 Summary Receiver Operating Characteristic (sROC) Analysis The sROC curves demonstrated excellent overall diagnostic accuracy for ER and HER2, with AUC values exceeding 0.95. Markers such as PD-L1, p53, and Ki-67 exhibited moderate diagnostic accuracy with wider confidence regions, reflecting variability across studies. Heterogeneity Analysis Significant heterogeneity was observed for several markers (I² > 60%). Subgroup analysis identified the following major contributors: • Differences in antibody clones • Variation in cut-off thresholds • Tumor heterogeneity across anatomical sites • Study design (retrospective vs prospective) Table 3. Heterogeneity and Subgroup Findings Parameter Observation Overall heterogeneity Moderate to high (I² = 52–78%) Major sources Antibody clone, cut-off variation Reduced heterogeneity Observed in organ-specific subgroup analyses Meta-regression Significant for tumor type and scoring system Publication Bias Assessment using Deeks’ funnel plot asymmetry test did not demonstrate significant publication bias for most major markers (p > 0.10). Mild asymmetry was observed in studies evaluating proliferation markers, likely reflecting selective reporting. Key Findings Summary • Hormone receptor markers and HER2 show high diagnostic accuracy and reliability • PD-L1 demonstrates moderate accuracy with substantial variability • Ki-67 and p53 require standardized scoring systems • Significant heterogeneity highlights the need for methodological harmonization Figure 2. Forest plot showing pooled sensitivity and specificity of immunohistochemical markers across the included diagnostic accuracy studies. Individual study estimates with 95% confidence intervals are displayed along with the pooled estimates derived using a random-effects model. Figure 3. Summary receiver operating characteristic (sROC) curve illustrating the overall diagnostic accuracy of immunohistochemical markers in oncology. The summary point represents the pooled sensitivity and specificity, with the shaded region indicating the 95% confidence region.

The present systematic review and meta-analysis provides a comprehensive evaluation of the diagnostic accuracy of commonly used immunohistochemical (IHC) markers across a broad spectrum of malignancies. By synthesizing evidence from 128 studies encompassing more than 24,000 tumor samples, this analysis offers quantitative insight into the strengths and limitations of IHC markers that are routinely applied in oncologic pathology. Comparison with Existing Literature Our findings demonstrate that hormone receptor markers, particularly estrogen receptor (ER) and progesterone receptor (PR), exhibit high pooled sensitivity and specificity in breast carcinoma. These results are consistent with previously published guideline-driven studies and reinforce the established role of ER and PR as reliable diagnostic and predictive biomarkers in breast cancer management [23,24]. Similarly, HER2 showed excellent diagnostic performance with the highest diagnostic odds ratio and area under the sROC curve, corroborating earlier reports that emphasize the robustness of HER2 immunohistochemistry when standardized scoring systems are applied [25]. In contrast, proliferation and tumor suppressor markers such as Ki-67 and p53 demonstrated moderate diagnostic accuracy with substantial inter-study heterogeneity. This variability mirrors findings from earlier observational and narrative reviews, which have highlighted inconsistencies in scoring methods, cut-off thresholds, and interpretative criteria as major contributors to discordant results [26,27]. Unlike hormone receptors, these markers are often used as adjuncts rather than definitive diagnostic tools, and our pooled estimates quantitatively support this auxiliary role. The diagnostic accuracy of PD-L1 in non-small cell lung carcinoma (NSCLC) was found to be moderate, with considerable heterogeneity across studies. This observation aligns with recent literature emphasizing the complexity of PD-L1 testing, where factors such as antibody clone selection, tumor proportion score cut-offs, and intratumoral heterogeneity significantly influence results [28,29]. While PD-L1 remains a critical predictive biomarker for immunotherapy, its diagnostic reliability continues to be context-dependent, as reflected in our analysis. Heterogeneity and Methodological Considerations A notable finding of this meta-analysis was the presence of moderate to high heterogeneity across most markers. Subgroup and meta-regression analyses identified antibody clone variability, scoring systems, tumor type, and study design as major sources of heterogeneity. These findings are in agreement with prior diagnostic accuracy reviews, which have underscored the lack of methodological uniformity in IHC studies as a persistent challenge [30]. The variability in cut-off values and subjective interpretation of staining intensity further complicates cross-study comparisons. Such methodological diversity underscores the need for rigorous standardization of pre-analytical, analytical, and post-analytical phases of IHC testing, as advocated by international pathology organizations [31]. Clinical Implications From a clinical standpoint, the results of this study reinforce the reliability of ER, PR, and HER2 immunohistochemistry in guiding diagnostic classification and therapeutic decision-making, particularly in breast oncology. Their high diagnostic accuracy supports continued reliance on these markers as core components of routine diagnostic panels. Conversely, markers such as Ki-67, p53, and PD-L1 should be interpreted with caution and within the broader clinical and morphological context. Given their moderate diagnostic performance and susceptibility to variability, these markers are best utilized as complementary tools rather than standalone diagnostic determinants. For PD-L1 in particular, standardized testing protocols and harmonization of scoring systems are essential to ensure consistent patient selection for immunotherapy. The findings also highlight the importance of organ-specific marker panels rather than universal application of individual IHC markers. Tailored diagnostic algorithms that integrate histomorphology, IHC, and molecular testing may improve diagnostic precision and reduce inter-observer variability. Strengths and Limitations The strengths of this study include a large pooled sample size, adherence to PRISMA-DTA methodology, and use of robust statistical models to estimate diagnostic accuracy. However, certain limitations must be acknowledged. The inclusion of predominantly retrospective studies may introduce selection bias. Additionally, incomplete reporting of antibody clones and cut-off values in several studies limited the depth of subgroup analyses. Publication bias, although minimal, cannot be entirely excluded. Future Directions Future research should focus on prospective, multicenter diagnostic accuracy studies with standardized IHC protocols and transparent reporting. Integration of digital pathology and artificial intelligence-assisted scoring may further enhance reproducibility and diagnostic consistency. Moreover, combined analyses of IHC markers with molecular and genomic data may provide a more holistic approach to cancer diagnosis and classification. In summary, this meta-analysis confirms that while several IHC markers demonstrate high diagnostic accuracy in specific oncologic settings, others exhibit variable performance influenced by methodological and biological factors. These findings emphasize the necessity for standardization, context-specific interpretation, and integration of IHC within multimodal diagnostic frameworks to optimize oncologic care.

This systematic review and meta-analysis demonstrates that immunohistochemical markers continue to play a pivotal role in oncologic diagnosis; however, their diagnostic accuracy varies considerably depending on the marker and tumor context. Hormone receptor markers and HER2 exhibit consistently high sensitivity and specificity, supporting their established role as reliable diagnostic and predictive tools. In contrast, markers such as Ki-67, p53, and PD-L1 show moderate diagnostic performance with significant inter-study heterogeneity, largely attributable to methodological variability and tumor heterogeneity. These findings highlight the need for standardized immunohistochemical protocols and context-specific interpretation to optimize diagnostic accuracy and clinical utility in oncology. Take-Home Messages • Immunohistochemistry remains indispensable in modern oncologic pathology, particularly for tumor classification and therapeutic decision-making. • ER, PR, and HER2 demonstrate high diagnostic accuracy, reinforcing their role as core markers in breast cancer diagnostics. • Ki-67, p53, and PD-L1 show moderate accuracy, necessitating cautious interpretation alongside histomorphology and clinical findings. • Significant heterogeneity exists across studies due to differences in antibody clones, scoring systems, and cut-off values. • Standardization of IHC methodologies is essential to improve reproducibility and diagnostic reliability. • Organ-specific IHC panels and multimodal diagnostic approaches may enhance accuracy and reduce diagnostic ambiguity.

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