Short summary

The aim of this project is To investigate the positive predictive value (PPV) of a TTP diagnosis registration in the Danish National Patient Registry (DNPR) in order to establish a population-based nationwide registry. A Danish nationwide TTP cohort will allow us to study a wealth of outcomes in future research.

Rationale

Thrombotic thrombocytopenic pupura (TTP) is a rare blood disorder in which clumping platelets cause clots in small blood vessels throughout the body. The condition can be hereditary or acquired (aTTP).

Survival for TTP patients is favourable, but relies on early diagnosis and treatment in the form of plasma exchange. However, patients with aTTP can be misdiagnosed, for example with Evans Syndrome (ES), the combination of autoimmune haemolytic anaemia (AIHA) and immune thrombocytopenia (ITP).

A Danish nationwide TTP cohort will allow examination of a wealth of outcomes such as cardiovascular morbidity, renal morbidity, osteoporosis and fractures due to steroid exposure, psychiatric morbidity, dementia, as well as detailed survival outcomes considering also comorbidity. Before embarking on the large-scale cohort study with multiple potential sub-studies it is necessary to do a validation study of Danish routine health data of TTP diagnosis registrations.

This study will validate diagnosis registrations of the ICD-10 TTP diagnosis code (M311A) as well as the combination of AIHA and ITP registrations (i.e. Evans syndrome) occurring 1 January 2000 through 2019.

Description of the cohort

Patients eligible for evaluation in this study are registered in the Danish National Patient Registry (DNPR) during 2000-2019 with the ICD-10 diagnosis code for TTP (M311A) or the ICD-10 diagnosis suggestive of Evans syndrome (ES) (D693 combined with one of the following - D591/D594/D594C/D598/D599/D599A).

Data and biological material

The validation will be based on data from medical files and laboratory values as gold standard and will cover all Danish departments of Haematology. From the medical files, the most correct diagnosis will be classified using a standardized algorithm. In addition, some baseline data will be collected such as diagnostic work-up, treatment (plasma exchange (including number and days), rituximab, others), ADAMTS13 results, complications, and cause of death.

Collaborating researchers and departments

Department of Haematology, Odense University Hospital

• Professor Henrik Frederiksen
• MD, PhD Dennis Lund Hansen