3-Day Surprise Question To Predict Survival Rates in Advanced Cancer Patients
Predicting survival rates in cancer patients with grave severity is crucial for both the patient, family, and doctors. Knowing this can help everyone adjust to the treatment that will be offered. If the unfortunate news is given, this can also help the patient experience a “good death”, where his or her final wishes are accommodated and pain is minimized. Today, although there are many technologies that can help with the early detection of diseases, many cancer patients still suffer from poor and inaccurate prognosis.
What is the Palliative Prognosis Score?
The Palliative Prognosis Score or (PaP) is a palliative care study predictor model that is used as a tool for prognosis prediction. It is often combined with the Surprise Question (SQ) “Would you be surprised if this patient died in the next 12 months”. This method is important in predicting the prognosis of cancer patients over the course of the year.
The PaP uses the Karnofsky Performance Score (KPS) along with five other criteria to find a ranking number ranging from 0 to 17.5. This value is used to assign patients to risk groups based on a 30-day survival probability. Unlike other prognostic scales, a heavy scoring weight in KPS revolved around the clinician’s ability to summarize the survival prediction. The palliative performance scale (PPS) is a scale ranging from 100 to 0 that correlates with KPS and can be used to predict actual survival rates in cancer patients.
Why is Accurate Prediction Important?
Although no one can predict the future, a good prediction of a cancer patient’s survival rate in the critical 3 days prior to death can help accommodate the patient’s final wishes. This will help the patient make the most out of his or her remaining days and receive the best end-of-life care.
Past studies have tried to predict the survival rate of cancer patients within 3 days. They looked at physical signs including breathing, pulse of the radial artery, peripheral cyanosis, drooping of nasolabial folds, and the patient’s palliative performance scale. While these physical signs were high in specificity, they turned out to have low sensitivity for death within 3 days. Therefore, the need to develop a better prognostic tool is of utmost importance.
The surprise questions, however, turned out to be highly sensitive tools for predicting prognosis. Both the 7-day surprise question and the 30-day surprise question showed great results.
“Would I be surprised if this patient died in the next 7 days?”
“Would I be surprised if this patient died in the next 30 days?
With this knowledge known, a study considered the 3-Day Surprise Question and if it could be a highly sensitive prognostic tool as well.
As originally published in Cancer Medicine, a study was performed on 1,896 patients wiith metastatic cancer, and focused on the Palliative Prognosis Score or (PaP). The study aims to find out the effectiveness of the 3 Day Surprise Question (3DSQ) in predicting the prognosis for terminal cancer patients with nearing death. It also aims to estimate the characteristics that caused inaccurate prediction.
The study is part of a multicenter prospective observational study that observes and records the dying process in advanced cancer patients in Japan. The 3DSQ question was answered by physicians of patients with a palliative performance scale of ≤20. The characteristics of patients who lived longer were also investigated using multivariate analysis.
This study was a secondary analysis of a previous multicenter prospective observational study. Its goal is to examine the dying process and end-of-life care in terminally ill cancer patients in Japan. The original study is called the “East Asian Collaborative Cross-Cultural Study to Elucidate the Dying Process” (EASED).
The included patients were adult individuals who were diagnosed with locally extensive or metastatic cancer and were admitted to PCUs. Patients who were scheduled for discharge or refused to be part of the study were excluded. Data were recorded by physicians on a standardized data-collecting sheet.
The data was analyzed for EASED. Patient information including age, cancer site, complication, metastasis, and treatment history was collected. History included the Eastern Cooperative Oncology Group Performance Status (ECOG PS and PPS) and all treatment received during the hospital stay. This includes oxygen therapy, sedation, and the presence of opioid administration.
Data about the physical signs were also gathered including Richmond Agitation Sedation Scale Score (RASS), response to visual and verbal stimuli, peripheral cyanosis, respiration with mandibular movement, bronchial secretions, and dysphagia of liquids. Data also included the patient’s body temperature, vital signs, respiratory rate, and clinical symptoms such as pain, fatigue, and edema. These were all evaluated using the Integrated Palliative Care Outcome Scale [IPOS].
The data collected were selected as representative prognostic factors. They asked physicians the 3DSQ, “Would you be surprised if this patient were to die within 3 days?”. The physicians had two answer choices, either “Not Surprised” or “Surprised”.
Data Analysis and Statistics
Patient status was recorded until death. The first day was set to “day one” during which the patient had PPS ≤20 and was defined as “death within 3 days” as death from day 1 to day 3. Two groups were created: “not surprised” group and “surprised” group according to the physician’s response.
- Among the 1886 patients, 1411 were evaluated.
- Among the 1179 patients (83.6%) patients who were in the “Not Surprised” Group, 636 died within 3 days.
- Among the 232 (16.4%) patients of the “Yes Surprised” Group, 194 patients lived longer than 3 days.
- The sensitivity, specificity, positive predictive value, and negative predictive value of the 3DSQ were 94.3% (95% confidence interval [CI]: 92.7% to 95.8%), 26.3% (95% CI: 24.8% to 27.6%), 53.9% (95% CI: 53.0% to 54.7%), and 83.6% (95% CI: 78.7% to 87.7%), respectively.
Multivariate analysis shows that palpable radial artery, absent respiration with mandibular movement, and SpO2 opioid administration, and no continuous deep sedation as characteristics of patients who lived longer than expected.
Sensitivity and specificity along with positive and negative prediction values were calculated using the 2 x contingency table.
In order to find the factors of all patients who exceed the 3-day expected death, the study authors divided patients into four groups.
The first group or group A consists of patients whose physician answer “not surprised” and actually died within 3 days. Group B were patients whose physicians answered “not surprised” and did not die within 3 days. Group C are patients whose physicians answered “surprised” and died within 3 days. The last group, group D are patients whose physicians answered “surprised” but did not actually die in 3 days. They performed a Cochran-Armitage trend test for ordinal variables and used Fisher’s exact test for categorical variables to identify factors in the “Lived Longer Group”.
Oncology Related Tools
- Opioid Conversion Calculator
- Updated Advanced Opioid Conversion Calculator
- Nonsteroidal anti-inflammatory drugs (NSAID) Selection Tool
- Absolute Neutrophil Count Calculator
- Body Surface Area (BSA) Multi-Calc
- Carboplatin AUC Calculator
- Carboplatin AUC – Updated Version
- Urinary Indices, Renal Failure Index (RFI) and Fractional Excretion of Sodium (FE-NA)
- Creatinine Clearance (CRCL) – Standard Calculator
- Creatinine Clearance Multi-Calc – All of the latest research
- Patient Controlled Analgesia (PCA) Settings
- Intravenous Antineoplastic Agents – Administration Guidelines
- Therapeutic Drug Levels
- Beers Criteria for potentially inappropriate medications
- Allergic response? 12-step desensitization protocol
- Protein requirements calculator
- Basal Metabolic Rate (BMR) Multi-calc (Estimate caloric requirements)
- Irritable Bowel Syndrome Treatment Options
- Common Anti-emetics
- Fall Assessment – Berg Balance Scale
- Quality Of Life In Adolescent Cancer Survivors
- Cancer Opioid Risk Score
- Oncology-Specific Opioid Risk Calculator In Cancer Survivors
- 3D MRI for Non-invasive Ocular Proton Therapy of Uveal Melanomas
- Sexual Dysfunction in Prostate Cancer Patients
- 3-Day Surprise Question To Predict Survival Rates in Advanced Cancer Patients