ESMO Asia 2016: Study Validates Set of Six Adaptable Prognosis Prediction Models for Patients With Cancer in Palliative Care Settings
A routine blood test may predict how long patients with cancer in palliative care will survive, researchers reported at the ESMO Asia 2016 Congress in Singapore.
“Cancer patients in palliative care want honest and accurate prognostic information but this information needs to be shared sensitively and in a way that respects their desire to maintain hope,” said lead author Dr. Yu Uneno, an oncologist at Kyoto University, Japan.
“Patients with advanced cancer and their families have to make decisions about treatment, where to spend the end of life, and when to discontinue palliative chemotherapy,” added Dr. Uneno. “Continuing ineffective therapy increases life-threatening adverse events, reduces quality of life, delays hospice referral, and deprives patients of the chance to die in their preferred place. Accurately predicting prognosis improves end-of-life care for cancer patients and their caregivers.”
Survival evaluations can determine whether or not pharmacologic treatment should be given. Cytotoxic chemotherapy would rarely be prescribed in a patient unlikely to survive beyond several weeks because of its potential side effects. The sedative midazolam is used for symptom relief in palliative care settings, but tolerance can develop if administered for 2 weeks or longer. Chronic midazolam treatment could therefore be recommended only for patients likely to die within a few weeks, and be contraindicated when predicted survival was longer than 1 month.
Previous models for predicting prognosis used subjective conditions such as dyspnea and delirium which may be scored differently by clinicians. These conditions were assessed once (at the start of treatment, for example), limiting the use of the models to that time point.
Validating the SAP Models
The current Six Adaptable Prognostic (SAP) models use three laboratory measurements (albumin, neutrophil, lactate dehydrogenase) which are routinely monitored in daily clinical practice with a blood test. The models can be used at any time point after the initiation of treatment—an important feature since a patient’s condition can change. The six models were developed in approximately 5,000 cancer patients receiving chemotherapy at Kyoto University Hospital. They predicted death within 1–6 months for patients with cancer receiving chemotherapy, allowing physicians to re-estimate prognosis at any time point after the initiation of chemotherapy.
The current study tested the predictive value of the models in cancer patients receiving palliative care. It was designed as a subanalysis of the Japan–prognostic assessment tools validation (J-ProVal) study, which compared the ability of four models to predict survival of advanced cancer patients in the real world.
This subanalysis included 1,015 patients, of whom 385 were based with palliative care teams in hospital, 464 were in palliative care units, and 166 were receiving palliative care services at home. The investigators performed receiver operating characteristic analysis to calculate the ability of the SAP models to predict death in patients with cancer in the palliative care setting. The area under the curve for predicting death within 1 to 3 months ranged from 0.75 to 0.80.
Dr. Uneno said, “We found that the SAP models had a good ability to predict that a patient would die in 1 to 3 months. The prediction was accurate in 75% to 80% of cases. The SAP models could be a promising decision aid for health-care professionals and patients. Accurate prediction of survival allows patients adequate time to prepare for their impending deathand is vital for planning effective palliative care.”
The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.
