Editor's Note: The "2024 CSCO Digestive Tract Tumor Standardized Treatment Workshop," co-hosted by the Chinese Society of Clinical Oncology, Beijing Xisike Clinical Oncology Research Foundation, and Hangzhou Oriental Clinical Oncology Research Center, was held in Shanghai from August 17-18, 2024. This workshop featured diverse learning methods, including lectures, discussions, and live surgical demonstrations, aimed at improving the standardized treatment of digestive tract tumors, reducing regional disparities, and disseminating new advancements and concepts. Oncology Frontier interviewed Dr. Jin Li, President of Shanghai GoBroad Cancer Hospital China Pharmaceutical University, Chairman of the CSCO Foundation, and Chairman of the CSCO Gastric Cancer Expert Committee, to discuss the highlights and significance of this workshop, as well as the potential and future of artificial intelligence in clinical research.

Oncology Frontier: The CSCO Digestive Tract Tumor Standardized Treatment Workshop has played a powerful role in continuing education for young doctors. Could you share the original intention and significance of establishing this program?

Dr. Jin Li: First of all, thank you for your attention to this CSCO Digestive Tract Tumor Standardized Treatment Workshop. Digestive tract tumors are currently among the most prevalent malignant tumors, including those originating in the esophagus, stomach, and intestines. Together, these three types of tumors account for over 1.2 to 1.3 million cases, possibly the highest among all malignant tumors. Therefore, focusing on digestive tract tumors is crucial for our overall cancer treatment efforts. Particularly, the prevalence of esophageal squamous cell carcinoma and gastric cancer is very high in China, with gastric cancer accounting for more than 45% of cases globally and esophageal cancer nearly half of the world’s cases. Although colorectal cancer in China has a relatively smaller global proportion, its incidence is rising annually, especially in economically developed regions like Beijing, Guangzhou, and Shanghai, due to changes in lifestyle and environment.

Therefore, addressing digestive tract tumors means addressing the most common cancer types in our country. We aim to benefit more patients by strengthening scientific research and improving standardized treatment levels, which is one of the main reasons for organizing this Digestive Tract Tumor Standardized Treatment Workshop.

The second reason is that China is vast, with significant regional economic disparities and uneven distribution of medical resources. Compared to the economically developed eastern coastal regions, the western and central regions have limited medical resources, and the level of standardized cancer treatment needs improvement. Even in the economically developed eastern regions, not all hospitals fully meet standardized treatment standards. In some grassroots hospitals, standardized treatment is either not fully implemented or not well-executed. Therefore, through workshops and academic activities like this, we aim to promote the improvement of standardized treatment levels, helping more patients live longer and better lives. This also has important significance for enhancing the academic level of clinical doctors and improving the quality of medical services.

Oncology Frontier: What are the main topics covered in this workshop? What are some highlights worth noting?

Dr. Jin Li: The main content of this workshop includes several key areas. First, we focus on the standardized treatment of gastric cancer, colorectal cancer, and esophageal cancer. In this section, we delve into how to conduct standardized diagnosis and treatment and provide interpretations of relevant guidelines, as guideline interpretation is the foundation of standardized treatment.

In addition, we will introduce some of the latest research advancements. For example, we will share significant research results or concepts that have a major impact on clinical research and practice, as presented at this year’s ASCO-GI, ASCO, and the upcoming ESMO conference. This helps participants stay up-to-date with the latest developments and apply these research findings in their clinical practice, allowing patients to benefit from the most advanced treatment concepts and strategies.

Most of the attendees at this workshop are senior or associate senior healthcare professionals, for whom mastering the latest knowledge and treatment strategies is equally important. Of course, standardized treatment remains the main focus of our workshop, but we have also organized some MDT case discussions and surgical observation activities. Our workshop covers multiple fields, including surgery, internal medicine, and radiotherapy, and also includes essential skills for clinicians, such as interpreting pathology and imaging diagnoses. Additionally, we have introduced some methodologies in clinical research to enhance doctors’ ability to diagnose and treat patients and to conduct clinical research.

Overall, the main learning content of this workshop includes standardized treatment, cutting-edge advancements, clinical skills, and an introduction to clinical research methodologies.

Oncology Frontier: How is artificial intelligence technology being used in clinical research to accelerate the development and validation of new therapies? Are there any successful cases you can share?

Dr. Jin Li: In the field of artificial intelligence (AI), ChatGPT is undoubtedly a name familiar to everyone. It has significantly changed the way we work; for example, when writing articles or press releases, you can quickly generate a draft by inputting key points into ChatGPT, which we then revise, greatly reducing our workload. Similarly, this transformation has also benefited the medical field, particularly in clinical research. In the past, clinical research was highly complex and required extreme accuracy, placing a heavy workload on doctors. Coupled with the demanding daily clinical tasks, doctors often struggled to balance high-quality clinical research. However, the introduction of AI has provided a solution to this problem. For instance, in the assessment of adverse events (AEs), doctors previously had to review the Common Terminology Criteria for Adverse Events (CTCAE) individually to determine the severity of adverse events. Now, AI can perform this task directly, accurately determining AE severity, significantly reducing the cognitive burden and workload for doctors.

Furthermore, AI can play a role in various aspects, such as writing medical histories, recruiting patients, evaluating tumor efficacy, and data transmission and analysis, thereby comprehensively improving the efficiency of clinical research. As technology continues to advance, AI has been widely applied in fields like drones and autonomous driving, and its application in the medical industry has already begun, gradually penetrating into clinical research.

At Shanghai GoBroad Cancer Hospital, we have already introduced an AI-assisted clinical research system. During my tenure at Fudan University Shanghai Cancer Center and Tongji University Shanghai East Hospital, I began developing a fully intelligent clinical trial data platform. After continuous and relentless efforts, our system has evolved into a comprehensive clinical trial management platform composed of seven subsystems, achieving precise and timely data transmission, avoiding errors caused by manual entry, and improving the quality of clinical research. Notably, our system uses advanced middle-office transmission technology, enabling automatic data collection and quality control. This means we can analyze data quality in real time during the research process, rather than waiting until the study is completed for evaluation. This also reduces the on-site verification work of CRCs (Clinical Research Coordinators), lowering clinical operational costs.

In summary, AI has broad application prospects in future clinical research and practice. It not only reduces the workload for doctors and improves research efficiency but also ensures data accuracy and research quality. We believe that as technology continues to mature and improve, AI will play an increasingly important role in clinical research.

Oncology Frontier: What value and challenges do you see for AI in the future of oncology treatment? Given the opportunities brought by AI, do you and your team have further strategies in place?

Dr. Jin Li: The main challenge AI faces in the future is the difficulty in collecting big data and sharing hospital data. Hospital data cannot easily leave the premises, which is a pain point in the global medical AI field. Although we have used middle-office technology to collect clinical trial data, the external transmission of non-clinical trial data within hospitals remains restricted. To solve this problem, some technology companies have explored the possibility of privacy computing technology with us. This technology, similar to the privacy design of digital currency, allows data to be computed within the hospital, while the computational results can be aggregated in the cloud without the need to remove the original data from the hospital. This approach ensures data security while enabling effective data utilization.

Through privacy computing, we hope to integrate data from various hospitals to form a large big data foundation, providing strong support for AI’s precise decision-making. After all, the accuracy of medical decisions often relies on comprehensive data analysis. For example, by analyzing the decisions and treatment outcomes of doctors nationwide, we can identify which treatment strategies are most effective for specific patient populations. This large-scale data analysis is AI’s strength. However, AI cannot solve all problems; it requires continuous adjustment and optimization based on human wisdom and experience. Through AI analysis, we can identify shortcomings and areas for improvement in clinical practice, guiding doctors to make more scientific and reasonable decisions. This combination of human and machine will drive the medical field towards a more intelligent and standardized direction.

In summary, the combination of privacy computing and AI has the potential to break down barriers to hospital data sharing, providing more comprehensive and accurate data support for medical decision-making. At the same time, we must recognize the limitations of AI and continuously explore new models of human-machine collaboration to promote the continuous progress and development of the medical field.

Oncology Frontier: What do you believe is the significance of holding the CSCO Digestive Tract Tumor Standardized Treatment Workshop for the diagnosis and treatment of digestive tract tumors in China?

Dr. Jin Li: The core significance of this workshop is to promote the improvement of standardized treatment levels for digestive tract tumors, ensuring that it becomes deeply rooted in the hearts of every doctor and is practically reflected in every step of the treatment plan they formulate for each patient. Only in this way can we ensure that patients receive the best treatment outcomes and optimal recovery.

To achieve this, we have carefully organized relevant course content, aiming to enhance the professional skills of participating doctors through this learning platform. The workshop has received recognition from many leading experts, such as Professors Cai Sanjun and Shen Lin, who emphasized that the workshop should not be a one-time event but rather a series of ongoing courses. We plan to regularly host workshops, each lasting 2 to 3 days, providing intensive and efficient training to help doctors continuously improve themselves and strengthen their practical abilities.

At the same time, to expand the influence of the workshop and benefit more doctors, we have also specially recorded and edited the content of each workshop into videos. These videos will be publicly released on online platforms in the future, allowing doctors who could not attend in person to learn online and continuously improve their professional skills. Through this combination of online and offline methods, we are committed to widely disseminating academic content and standardized treatment concepts, enabling more doctors to master advanced diagnostic and treatment techniques and concepts, and providing better medical services to patients.

Dr. Jin Li

• President of Shanghai GoBroad Cancer Hospital, China Pharmaceutical University
• Lifetime Professor at Tongji University Shanghai East Hospital
• Chairman of the Asian Oncology Alliance (FACO)
• Chairman of the CSCO Foundation
• Chairman of the Oncology Clinical Research Committee, China Association of Medical Promotion
• Deputy Chairman of the Oncology Expert Committee for Capacity Building and Continuing Education, National Health Commission
• Former President of the Chinese Society of Clinical Oncology (CSCO)
• Chairman of the CSCO Gastric Cancer Expert Committee
• Deputy Editor-in-Chief of Cancer Science