The challenge of individualised risk assessment and therapy planning in elderly high-risk myelodysplastic syndromes (MDS) patients

Myelodysplastic syndromes (MDS) represent one of the most frequent and serious haematologic diseases of the elderly. Effective therapies exist ranging from best supportive care to haematologic stem cell transplantation (HSCT). Decision making, however, is rather complex in this group of patients because ageing is a multidimensional process involving not only physiological changes but also changes in functional, social, emotional and cognitive capacities. All these factors can have a significant impact on the efficacy and tolerability of a potential therapy and therefore have to be thoroughly assessed before deciding on individual treatment regimens. Risk assessment tools are available both to classify the stage and prognosis of MDS and to meet the needs of elderly patients. A tool explicitly focussing on elderly MDS patients, however, is still missing. The current report approached this issue by combining the well established MDS-risk score ‘International Prognostic Scoring System’ (IPSS) with the ‘Multidimensional Geriatric Assessment’ (MGA). As decision making is most complex in high-risk MDS patients, the new algorithm is presented exemplarily for this group of patients. In a first step, MDS-related risk is identified using IPSS, in a second step, patients are assigned to one of three risk categories of the MGA (go-go/fit, slow-go/vulnerable, no-go/frail). While go-go patients might be subjected to therapies comparable to those given to younger patients, in no-go patients, a palliative therapy combined with best supportive care will probably be most appropriate. In slow-go patients, age-related life expectancy taken from public age statistics should be compared to the MDS-related life expectancy. Based on this combined assessment procedure and also on treatment tolerance in terms of the expectations/wishes of the patient and his/her family, an individualised therapeutic approach should be developed. Specific treatment recommendations for these three groups of patients are given, including HSCT, azanucleosides and best supportive care. To illustrate its practicability, i.e. the implementation of the novel algorithm in clinical practice, the case of an elderly high-risk MDS patient is presented and discussed in detail. This new algorithm will facilitate the identification of the very particular needs and conditions of elderly MDS patients in clinical practice. Based on this, individually tailored therapeutic approaches can be developed—the prerequisite for the best possible clinical outcome.