HTTP Interface and External Systems for Solid Tumor Clinical

Data Characteristics for This Category

Solid tumor clinical trial prescreening data originates primarily from medical literature, clinical trial registries (e.g., ClinicalTrials.gov), electronic medical record systems, gene sequencing reports, and pathology reports. Update frequencies vary; clinical trial registration information might update weekly, while gene sequencing or pathology reports generate during patient diagnosis or treatment. Data structures are typically complex, containing both structured and unstructured information. Structured data includes patient demographics, diagnosis dates, and tumor staging (e.g., TNM staging), often presented in tabular form. Unstructured data encompasses text information like pathological descriptions, imaging report conclusions, and gene mutation site descriptions. Fields may involve tumor type (e.g., "lung adenocarcinoma"), gene mutations (e.g., EGFR L858R), and PD-L1 expression status (e.g., PD-L1 TPS >= 50%). Units are typically percentages, copy numbers, or text descriptions.

Constraints Imposed by These Characteristics on the "HTTP Interface and External Systems" Component

The diversity and complexity of solid tumor data impose specific requirements on HTTP interfaces. First, unstructured text data (like pathology reports) requires interfaces to support large text transfers and may need additional preprocessing services for structured extraction. Second, the high update frequency of clinical trial registration data demands efficient data synchronization mechanisms from HTTP interfaces to prevent information lag from affecting prescreening accuracy. The heterogeneous nature of data sources means a unified interface protocol is necessary to integrate data from different systems—for example, obtaining basic patient information from an electronic medical record system and then gene data from a gene sequencing platform. Additionally, sensitive data transfers involving patient privacy must use HTTPS protocol encryption and undergo strict authentication and authorization controls. The specificity of fields, such as tumor staging and gene mutation sites, requires interface parameter design to precisely map these medical concepts and support complex query condition combinations.

Configuration Guidelines

Configuration Item	Recommended Value	Rationale
`requestTimeout`	`60000 ms`	Handles long-running requests due to slow external system responses or large data volumes, preventing interruptions.
`maxConnections`	`100`	Accounts for high concurrency scenarios, needing to process multiple patient prescreening requests simultaneously to ensure throughput.
`payloadSizeLimit`	`50 MB`	Accommodates JSON/XML request bodies containing long text pathology reports or multiple gene test results.
`authHeader`	`Bearer <token>`	Most external systems use OAuth2 or JWT authentication, ensuring data transfer security.
`retryAttempts`	`3`	Addresses occasional network fluctuations or service unavailability in external systems, improving request success rates.
`contentType`	`application/json`	Clinical data interfaces primarily use JSON format for data exchange, facilitating parsing and serialization.

Common Pitfalls

An HTTP request returning a getaddrinfo ENOTFOUND error typically indicates external system domain resolution failure or an address misspelling.
Boolean data parsed from an HTTP component becoming null in a conditional judgment component might result from improper data type conversion, causing the boolean value to be misinterpreted as neither true nor false.
An HTTP request failing with a 406 Not Acceptable error may occur if the Accept field in the request header does not match the content types supported by the external system.

How to Verify Configuration

Execute multiple requests to core patient data query interfaces. Check if the returned data structure, field values, and critical medical information like tumor staging and gene mutations align with expectations.
Simulate scenarios where external systems are temporarily unavailable or respond with delays. Observe how FastGPT handles request timeouts and retries, ensuring the system has sufficient fault tolerance.
Use a packet capture tool or logs to verify if HTTP request headers like Content-Type and Authorization are set correctly, confirming security and format compliance.

The values provided are common starting points and should be measured against specific samples.

Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-21.