Delirium deteriorates the quality of life in patients with cancer, but is frequently underdiagnosed and not adequately treated. In this study, we evaluated the occurrence of delirium and its risk factors in patients admitted to the hospital for treatment or palliative care in order to develop a prediction model to identify patients at high risk for delirium. In a period of 1.5 years, we evaluated the risk of developing delirium in 574 consecutively admitted patients with cancer to our academic oncology department with the Delirium Observation Screening Scale. Risk factors for delirium were extracted from the patient's chart. A delirium prediction algorithm was constructed using tree analysis, and validated with fivefold cross‐validation. A total of 574 patients with cancer were acutely (42%) or electively (58%) admitted 1733 times. The incidence rate of delirium was 3.5 per 100 admittances. Tree analysis revealed that the predisposing factors of an unscheduled admittance and a metabolic imbalance accurately predicted the development of delirium. In this group the incidence rate of delirium was 33 per 100 patients (1:3). The AUC of the model was 0.81, and 0.65 after fivefold cross‐validation. We identified that especially patients undergoing an unscheduled admittance with a metabolic imbalance do have a clinically relevant high risk to develop a delirium. Based on these factors, we propose to evaluate preventive treatment of these patients when admitted to the hospital in order to improve their quality of life.

130 Background: Delirium is a distressing experience for patients with cancer. Incidence rates of delirium vary between 5 and 88 percent. We studied the incidence of delirium on our medical oncology ward, along with its predisposing and precipitating factors, in order to identify patients who may benefit from screening and early interventions. Methods: We evaluated patients admitted to our medical oncology ward between January 2011 and June 2012 for delirium. In this period a screening program with the Delirium Observation Screening Scale was initiated. Risk factors for delirium were extracted from the patient’s chart. We developed a prediction model to identify patients who are at risk to develop delirium and optimized this model with a cohort of patients with a delirium diagnosed between June 2012 and September 2013. Results: 1,733 admittances of 574 individual patients were recorded in the study period. Sixty episodes of delirium were identified in 52 patients. The patients had a mean age of 60 years, and most patients (70%) had advanced cancer. The most prevalent predisposing and precipitating factors were age >70, drug intoxication, infection and metabolic imbalances (abnormalities in sodium, potassium, calcium, albumin or glucose levels), which were present in 21, 25, 22, and 18 percent, respectively. The prediction model revealed that patients who were electively admitted had a very low risk to develop delirium (1%), but patients admitted for an emergency with at least one metabolic abnormality, such as hyperkalemia, were at high risk for developing a delirium (delirium risk 33%). Conclusions: Based on our analyses for risk factors of delirium, we developed a new prediction model for the risk for delirium in patients with cancer admitted to an oncology ward that may be used for targeted screening and to study preventive therapy in order to improve their quality of life.

231 Background: Delirium is highly prevalent in patients with advanced cancer. Patients experiencing delirium may require pharmacological treatment to reduce distressing symptoms. Atypical antipsychotics, like olanzapine, are potentially safer and more effective than haloperidol, but no phase III RCTs are reported in patients with advanced cancer. Methods: Hospitalized patients with advanced cancer diagnosed with delirium ( DSM-IV-TR criteria) were randomly assigned centrally (1:1) to olanzapine or haloperidol. Dosages were up-titrated. Primary endpoint was delirium resolution rate (DRR), defined as Delirium Rating Scale-Revised-98 (DRS-R-98) total severity score < 15.25 points and ≥ 4.5 points reduction. Secondary endpoints: time to recovery, grade ≥ 3 side effects (Common Terminology Criteria for Adverse Events version 3.0), and distress (Delirium Experience Questionnaire). The study was powered to increase DRR with 25% for olanzapine compared to haloperidol. Results: Between January 2010 and June 2016, 100 of the anticipated 200 patients were enrolled in the study from 6 sites in the Netherlands and randomly assigned to olanzapine (n = 50) or haloperidol (n = 50). Baseline characteristics were well balanced. Interim analysis showed a difference in DRR of -12.2% (95% confidence interval (CI) = -32.0%- 7.4%); 45% for olanzapine (95% CI 31.0-58.8) vs 57% for haloperidol (95% CI 43.3-71.0), P = 0.22).Time to recovery was 4.5 days in the olanzapine arm vs 2.8 days in the haloperidol arm (P = 0.20). There was no difference in grade ≥ 3 side effects between both arms (OR 0.44, 95% CI 0.14-1.40; P = 0.16). Mean level of distress in patients was 2.1 (SD 1.4) for olanzapine vs 2.3 (SD 1.4) for haloperidol (P = 0.80). Formal interim futility analysis indicated a conditional power of 0.086, implying a very low likelihood (8.6%) of reaching the expected DRR superiority rate of 25% for olanzapine. Therefore, the study was prematurely terminated. Conclusions: No difference in efficacy and side effect profile was observed between haloperidol or olanzapine treatment for delirium in patients with advanced cancer. Clinical trial information: NCT01539733.