Breast cancer is the most common malignancy and a major cause of cancer-related deaths among women (1, 2). Research has indicated that breast cancer patients turn to complementary medicine to relieve side effects from cancer treatments and improve their quality of life (3–5). Chinese herbal medicine (CHM) is a frequently used form of complementary medicine, with its effectiveness dependent on accurate Chinese medicine (CM) syndrome differentiation (6). As such, there is a pressing need to standardize the CM syndrome differentiation and treatment of breast cancer to enhance therapeutic outcomes in clinical settings. An essential step in advancing the understanding of early breast cancer CM syndromes involves establishing a standard for CM syndrome differentiation and quantifying as well as standardizing the syndrome differentiation process.

In our clinical practice, we noted variations in CM syndromes in response to different treatments for breast cancer and pointed out the differentiation of CM syndromes across various treatment stages (7). Researchers have also indicated that syndrome differentiation by treatment stage in breast cancer exemplifies the integration of disease and syndrome concepts (8). As such, we further utilized a systematic review (9), a clinical study (10), and a Delphi study (11) to establish diagnostic criteria for CM syndrome differentiation among different treatment stages of early breast cancer. This diagnostic criterion clearly defines primary and secondary CM syndrome diagnostic conditions through the comprehensive use of multiple statistical methods, data mining, and expert consultation meetings. Clinical validation is crucial in assessing the clinical applicability of CM syndrome research findings. However, no confirmatory tests have been conducted in published studies on breast cancer CM syndrome, leading to limited credibility and acknowledgment of the research outcomes.

To rigorously verify the diagnostic efficacy of these criteria, this study conducted a prospective, multicenter, large-sample clinical investigation to gather clinical case information on early breast cancer. Diagnostic evaluation tests were then performed to offer evidence-based medical support in clinical practice and enhance the credibility of stage syndrome differentiation.

This study was approved by the Ethics Committee of Guangdong Provincial Hospital of Chinese Medicine (approval no. ZE2022-142-01) before recruitment commenced. Other centers received ethics approval from their centers. All participants provided written informed consent. This study was registered with the Chinese Clinical Trial Registry under the registration number ChiCTR2200061022 on 15 June 2022.

This study was carried out in multiple centers from June 2022 to October 2023, including the hospitals located in South China (Guangdong, Hainan), East China (Shanghai, Jiangsu, Zhejiang), Central China (Hunan), and Southwest China (Chongqing). A total of 665 patients were initially approached for participation in this study. Among them, 17 patients did not provide informed consent, and seven were excluded because they did not meet the inclusion criteria. Ultimately, 641 eligible patients were included in the study. A total of 1141 case report forms were collected, as illustrated in Figure 1; the distribution of cases across centers is detailed in Figure 2.

In this multicenter prospective clinical study, we collected epidemiological data on CM syndromes to evaluate diagnostic tests, specifically assessing the diagnostic efficacy of CM syndrome differentiation criteria for early breast cancer. To the best of our knowledge, this is the first publication that verifies the CM syndrome diagnostic criteria in the context of breast cancer. This study contributes significantly to the standardization of clinical practice and offers a crucial reference for future investigations into the diagnosis of breast cancer syndromes.

The primary goal of establishing diagnostic criteria for CM syndrome is to facilitate their application in clinical practice and enhance standardization (13, 14). The scientific validation of these criteria is essential for their adoption and critical in assessing their validity and reliability. For instance, Luo (15) conducted a diagnostic test evaluation on Blood stasis syndrome, demonstrating high diagnostic effectiveness and greater reliability. Similarly, Zhou (16) evaluated the diagnostic threshold for coronary heart disease’s phlegm and dampness syndrome, improving the criteria’s diagnostic efficacy, operability, and repeatability. Despite these advances, many studies in CM syndrome research lack further validation (17), undermining the authority and recognition of their findings. This issue also pertains to breast cancer syndrome research (18–20).

Consequently, this study performs diagnostic tests on the newly established criteria for early breast cancer stage differentiation, addressing previous limitations and confirming the criteria’s effectiveness and enhanced scientific credibility.

The results demonstrate a high level of reliability in the diagnostic standards employed for evaluating the syndromes. Sensitivity and specificity are essential metrics in assessing diagnostic accuracy (21), based on the test’s inherent attributes. Sensitivity indicates the ability to avoid missed diagnoses, while specificity relates to reducing misdiagnoses. It is crucial to evaluate both metrics when analyzing diagnostic tests. However, relying solely on sensitivity and specificity may not provide a complete assessment; additional factors like accuracy and the Youden index should also be taken into account. The Youden index and likelihood ratios are composite indices that reflect both sensitivity and specificity (22). The positive and negative predictive values are significantly influenced by the disease’s prevalence (23). With constant sensitivity and specificity, the positive predictive value increases as prevalence rises, whereas the negative predictive value decreases. Thus, in cases where the disease prevalence is low, even highly sensitive and accurate diagnostic criteria may yield a low positive predictive value.

Conducting multicenter clinical research is the optimal approach for collecting comprehensive diagnostic data (24), but should be careful about data interpretation bias (25). Wang (26) conducted a multicenter cross-sectional study on damp-heat syndrome in diabetic coronary heart disease, including a broad array of research subjects to ensure representativeness. Currently, many CM syndrome studies, including those on breast cancer, are limited to one research institution or one research region (18, 27, 28). This limitation leads to sample selection bias and inadequate sample sizes, compromising the objectivity and evidential strength of the research (29). Additionally, some multicenter studies are restricted to specific areas, lacking nationwide representation. To address these issues, this study undertakes a large-scale, multicenter clinical study across various regions to gather epidemiological data, thereby enhancing the reliability and applicability of the research findings.

In addition, due to objective differences in the scale and patient flow of the participating centers, there were disparities in the number of cases ultimately contributed by each center, resulting in an inherent imbalance in the data. The International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) E9 (Statistical Principles for Clinical Trials) guideline suggests that exploring center effects is necessary when the sample size in each center is sufficient. In this diagnostic test study, where inter−center sample sizes varied considerably and the primary aim was to verify the generalizability of the diagnostic criteria, we focused on evaluating the overall performance of the criteria in the pooled population from all centers. Therefore, we ultimately did not perform an inter−center heterogeneity analysis.

The scientific establishment of diagnostic criteria for CM syndromes constitutes a foundational element in realizing the standardization and regularization of CM diagnosis and treatment. Historically, the absence of well-defined and universally accepted protocols for the development of these criteria has significantly impeded their formulation and subsequent dissemination. In 2023, the World Federation of Chinese Medicine Societies addressed this gap by drafting the “Guidelines on establishing diagnostic criteria of Chinese medicine syndromes” (30), which was informed by the preexisting technical framework for CM syndrome standard development. The guidelines delineate a comprehensive development process that encompasses literature review, expert consultation, clinical investigation, formulation of syndrome diagnostic criteria, and validation. Our research project has already undertaken relevant preliminary studies and is currently advancing the final phase of clinical validation in strict adherence to contemporary standard research methodologies, thereby exemplifying a robust paradigm for the development of CM syndrome standards. Further, the field of CM syndrome research remains replete with areas of inquiry that warrant further exploration. These include the objective diagnosis of CM syndromes, the elucidation of their scientific connotations, and the integration of CM syndromes with artificial intelligent (31, 32). These emerging frontiers of research are poised to catalyze our continued advancement in this domain.

Some limitations should be acknowledged. The lack of a recognized gold standard for reference and reliance on expert experience introduces an inevitable subjective bias, and this shortcoming also mirrors the broader methodological constraints currently faced in validating CM syndromes. Further, the lack of clear decision thresholds for each diagnostic test index prevents objective and accurate assessment of the diagnostic criteria. In this study, patients who did not receive endocrine therapy were excluded from enrollment. This exclusion underscores a gap in CM syndrome research for this population, limiting the diagnostic criteria’s applicability. The suboptimal diagnostic performance observed for certain syndromes may be attributed to their relatively small sample sizes, which also precluded further subgroup analysis. This underscores the need to enlarge the overall sample and achieve a more balanced distribution across syndromes in future work, thereby enhancing statistical power and robustness.

This multicenter prospective clinical study aimed to validate the diagnostic criteria for CM syndrome among different treatment stages in early breast cancer. The study collected substantial clinical data and performed a diagnostic evaluation test on the criteria for syndrome diagnosis. The results demonstrated high reliability in the diagnostic standards. Ultimately, the diagnostic test confirmed the authenticity, reliability, and clinical application value of CM syndrome differentiation criteria for early breast cancer. This research addressed a gap in verifying CM syndrome diagnostic criteria for breast cancer and significantly contributed to standardizing clinical practice. Further, this study lays a valuable foundation for future studies and enhances the understanding and application of CM syndrome in the context of breast cancer.