An increasing number of studies suggested that the tumor microenvironment exerts a substantial influence on the pathophysiology of pancreatic cancer. As a crucial component of the tumor microenvironment,the tumor stroma plays a pivotal role in the occurrence,development,and chemotherapy resistance of pancreatic cancer. By serving as a proxy for the interaction between tumor cells and the microenvironment,the tumor stroma ratio(TSR) has emerged as a focal point of investigation in recent years. At present,numerous studies show that a low TSR is a protective factor for the prognosis of resectable pancreatic cancer. Additionally, patients with a low TSR are more suitable for the gemcitabine and albumin-bound paclitaxel chemotherapy regimen. But these researches are not conclusive, and there is still a gap between guiding precision treatment. Further research and exploration are required. Integration of artificial intelligence deep learning models into traditional pathological and imaging assessments facilitates precise evaluation of the TSR. It can also enable stratification and precision treatment of pancreatic cancer patients based on this index.

An increasing number of studies suggested that the tumor microenvironment exerts a substantial influence on the pathophysiology of pancreatic cancer. As a crucial component of the tumor microenvironment,the tumor stroma plays a pivotal role in the occurrence,development,and chemotherapy resistance of pancreatic cancer. By serving as a proxy for the interaction between tumor cells and the microenvironment,the tumor stroma ratio(TSR) has emerged as a focal point of investigation in recent years. At present,numerous studies show that a low TSR is a protective factor for the prognosis of resectable pancreatic cancer. Additionally, patients with a low TSR are more suitable for the gemcitabine and albumin-bound paclitaxel chemotherapy regimen. But these researches are not conclusive, and there is still a gap between guiding precision treatment. Further research and exploration are required. Integration of artificial intelligence deep learning models into traditional pathological and imaging assessments facilitates precise evaluation of the TSR. It can also enable stratification and precision treatment of pancreatic cancer patients based on this index.

Objective To evaluate the outcome indicators in clinical research on TCM treatment for polycystic ovary syndrome(PCOS);To provide a theoretical basis for establishing the PCOS clinical core outcome indicator set.Methods Relevant clinical research about TCM treatment for PCOS was retrieved from CNKI,Wanfang Data,VIP,CBM,Embase,PubMed,Web of Science and Cochrane Library from 1st,Jan.2019 to 15th,Nov.2023.Research articles were screened based on predefined inclusion and exclusion criteria,and a comprehensive analysis was conducted on the extracted data.Results A total of 951 clinical studies were included(915 in Chinese and 36 in English),involving 86 369 patients,with 221 outcome indicators identified,and a total frequency of 8 991 occurrences.Analysis revealed that commonly used outcome indicators included hormone levels(such as luteinizing hormone,follicle-stimulating hormone,testosterone),overall efficacy rate,ovulation rate,pregnancy rate,TCM syndrome score,ovarian volume and insulin resistance index.However,there was considerable variation in the choice of indicators across different studies,and some indicators were misaligned with clinical needs,lacking a focus on long-term prognosis and safety.Conclusion Clinical research on TCM treatments for PCOS often demonstrates significant variability in outcome indicators,lack of clarity between primary and secondary indicators,disorganized description of indicators,diversity in the choice of measurement tools,and a lack of indicators for specific populations.These problems lead to difficulties in combining similar studies for meta-analysis and fail to provide high-level evidence-based clinical guidance.There is an urgent need to establish a core set of outcome indicators for clinical research on TCM treatment for PCOS.