Patients suffering from severe forms of Chronic Kidney Disease (CKD) are usually treated with either dialysis or transplantation. Dialysis can come in different forms, most typically haemodialysis or peritoneal dialysis. It is common for patients to switch between treatment modalities; this can occur when: a donor kidney becomes available for those on dialysis, when a transplant fails and a patient is required to begin dialysis, or a switch between the different types of dialysis is recommended. Clinicians and patients need to decide which treatment regimens are best for them given their personal medical history, clinical status, and lifestyle. It would be advantageous if this choice of treatment could also take into account potential treatment switches in the future. In this way, treatment decisions can be personalised to patients to provide an optimised treatment choice. This kind of decision making process can potentially provide better treatment for patients and improve cost-effectiveness in a healthcare system.
The intention of this project is to develop and internally validate a clinical prediction model for patients receiving Renal Replacement Therapy (RRT), taking into account changes in treatment modality. By providing patients and clinicians with as much information as possible about their condition and treatment options, models such as this have the potential to improve decision making processes given the patient’s individual characteristics and prognosis. This Multi-State Model (MSM) will account for how a patient may switch treatment throughout their time on RRT, which will allow clinicians and patients to understand the journey through these different treatments that they may take. This knowledge, combined with the experience of the clinician and the preferences of the patient, will allow more informed choices to be made. An internal validation of the model produced will provide evidence for its reliability and support its potential use in clinical practice.