Role of Microenvironment Analysis and MRI Radiomic Study in the Risk Stratification of Distant Metastases in Rectal Cancer

Data collection process in strict implementation of special management, the full name of quality control. Special personnel are responsible for collecting clinical images and pathological information of patients in the medical record system, and personal identification data will be used to identify and process, in order to protect the privacy of test patients/participants. At the same time, there is a special person responsible for quality control and source data verification. Participants use the project unified number as the unique identification code, personal data and case information by the sample management personnel input and save, the user only see the individual number, no longer show the participants' name and other personal information. Data dictionary that contains detailed descriptions of each variable used by the registry, including the source of the variable, coding information was built. Participants' sample information is stored electronically in a dedicated computer that is not used for other purposes and is provided with a password, which is only available to the person (1 person) who manages the sample. Participants' medical records will be kept at the hospital and will be accessible only to researchers; If necessary, members of the bidding organization, ethics committee or government management department may access the personal data of the participants according to the corresponding authority. The results of the study will be published as statistically analyzed data and will not contain any identifiable participant information.

The sponsor is responsible for implementing and maintaining quality assurance and quality control systems with written Standard Operating Procedures (SOPs) to ensure that trials are conducted and data are generated, documented (recorded), and reported in compliance with the protocol, good clinical practices (GCP), and the applicable regulatory requirement(s). The SOPs should cover system setup, installation, and use. The SOPs should describe system validation and functionality testing, data collection and handling, system maintenance, system security measures, change control,data backup, recovery, contingency planning, and decommissioning. The responsibilities of the sponsor, investigator, and other parties with respect to the use of these computerized systems should be clear, and the users should be provided with training in use. Noncompliance with the protocol,SOPs,GCP, and/or applicable regulatory requirement(s) by an investigator/institution, or by member(s) of the sponsor's staff should lead to prompt action by the sponsor to secure compliance.

According to the morbidity of LARC and the risk of distant metastasis, the sample size is 300, and the follow-up interval is at least 3 years.

Plan for missing data: If the proportion of missing data is very large, such as greater than 95%, the investigators can directly remove this field; At 50~95%, the investigators have two processing methods, one is to remove this field directly; another way is to turn the field into an indicator variable; that is the 0-1 variable. If the field is empty, the field is 0; Otherwise the field is 1. Between 5% and 50% : In this scenario, the investigators need to fill in the missing values. In the process of filling, there are two categories: simple filling and algorithm filling. Simple filling includes: 0 filling, mean filling, median filling, mode filling; Algorithm filling methods such as K Nearest Neighbors (KNN) filling, random forest filling and so on.

Statistics Statistical Product and Service Solutions (SPSS, version 26.0) and R software (version 4.0.5) were used for statistical analyses. Receiver operating characteristic (ROC) curve analysis was used to evaluate the optimum cutoff value of tumor stromal ratio (TSR) in discriminating DM risk based on the maximum Youden index. Heat maps showed the distribution of variables between patients with or without DM within 3 years. The independent DMFS risk factors were determined using Kaplan-Meier (K-M) curves and Cox regression analysis sequentially based on the data of the training cohort. Statistical significance was set at P<0.05. Inter-observer variability was assessed using κ statistics for categorical and ranked variables, and ICC for continuous variables.