Aims: choosing the optimal palliative lung radiotherapy regimen is challenging. Guidance from The Royal College of Radiologists recommends treatment stratification based on performance status, but evidence suggests that higher radiotherapy doss may be associated with survival benefits. The aim of this study was to investigate the effects of fractionation regimen and additional factors on the survival of palliative lung cancer radiotherapy patients.
Materials and methods: A retrospective univariable (n = 925) and multivariable (n = 422) survival analysis of the prognostic significance of baseline patient characteristics and treatment prescription was carried out on patients with non-small cell and small cell lung cancer treated with palliative lung radiotherapy. The covariates investigated included: gender, age, performance status, histology, comorbidities, stage, tumour location, tumour side, smoking status, pack year history, primary radiotherapy technique and fractionation scheme. The overall mortality rate at 30 and 90 days of treatment was calculated.
Results: univariable analysis revealed that performance status (P < 0.001), fractionation scheme (P < 0.001), comorbidities (P = 0.02), small cell histology (P = 0.02), ‘lifelong never’ smoking status (P = 0.01) and gender (P = 0.06) were associated with survival. Upon multivariable analysis, only better performance status (P = 0.01) and increased dose/fractionation regimens of up to 30 Gy/10 fractions (P < 0.001) were associated with increased survival. Eighty-five (9.2%) and 316 patients (34%) died within 30 and 90 days of treatment, respectively.
Conclusion: In this retrospective single-centre analysis of palliative lung radiotherapy, increased total dose (up to and including 30 Gy/10 fractions) was associated with better survival regardless of performance status.
Context: At our institution, clinical pathways capture physicians’ prognostication of patients being evaluated for palliative radiotherapy (PRT). We hypothesize a low utilization rate of long-course RT (LCRT) and stereotactic ablative radiotherapy (SAbR) among patients seen at the end-of-life, especially those with physician predicted poor prognosis.
Objective: To analyze utilization rates and predictors of LCRT and SAbR at the end-of-life.
Methods: A retrospective review was conducted on patients who were evaluated for PRT between January 2017 to August 2019 and died within 90 days of consultation. Binary logistic regression was used to identify predictors for utilization of LCRT (=10 fractions) and SAbR.
Results: A total of 1,608 patients were identified, of which 1,038 patients (64.6%) were predicted to die within a year. 693 patients (66.8%) out of 1,038 were prescribed LCRT or SAbR. On multivariate analysis, patients were less likely to be prescribed LCRT if treated at an academic site (OR 0.30; 95% CI 0.23-0.39; p<0.01) and treated for bone metastases (OR 0.08; 95% CI 0.05-0.11; p<0.01) or other non-brain/non-bone metastases (OR 0.19; 95% CI 0.13-0.30; p<0.01). SAbR was less likely to be prescribed among patients predicted to die within a year (OR, 0.09; 95% CI 0.06-0.16; p<0.01), treated for bone metastases (OR, 0.13; 95% CI 0.07-0.22; p<0.01), with poor performance status (OR, 0.51; 95% CI 0.31-0.85; p=0.01), and with a breast primary (OR, 0.35; 95% CI 0.15-0.82; p=0.02).
Conclusion: Despite most patients predicted to have a limited prognosis, LCRT and SAbR were commonly prescribed at the end-of-life.
Background: Symptom assessment is essential in palliative care, but holds challenges concerning implementation and relevance. This study aims to evaluate patients’ main symptoms and problems at admission to a specialist inpatient palliative care (SIPC) ward using physician proxy- and patient self-assessment, and aims to identify their prognostic impact as well as the agreement between both assessments.
Methods: Within 12 h after admission, palliative care specialists completed the Symptom and Problem Checklist of the German Hospice and Palliative Care Evaluation (HOPE-SP-CL). Patients either used the new version of the minimal documentation system for patients in palliative care (MIDOS) or the Integrated Palliative Care Outcome Scale (IPOS) plus the Distress Thermometer (DT).
Results: Between 01.01.2016–30.09.2018, 1206 patients were included (HOPE-SP-CL 98%; MIDOS 21%, IPOS 34%, DT 27%) where of 59% died on the ward. Proxy-assessment showed a mean HOPE-SP-CL Total Score of 24.6 ± 5.9 of 45. Most frequent symptoms/problems of at least moderate intensity were weakness (95%), needs of assistance with activities of daily living (88%), overburdening of family caregivers (83%), and tiredness (75%). Factor analysis identified four symptom clusters (SCs): (1) Deteriorated Physical Condition/Decompensation of Home Care, (2) Emotional Problems, (3) Gastrointestinal Symptoms and (4) Other Symptoms. Self-assessment showed a mean MIDOS Total Score of 11.3 ± 5.3 of 30, a mean IPOS Total Score of 32.0 ± 9.0 of 68, and a mean distress of 6.6 ± 2.5 of 10. Agreement of self- and proxy-assessment was moderate for pain ( = 0.438) and dyspnea ( = 0.503), fair for other physical ( = 0.297 to 0.394) and poor for psychological symptoms ( = 0.101 to 0.202). Multivariate regression analyses for single symptoms and SCs revealed that predictors for dying on the SIPC ward included impaired ECOG performance status, moderate/severe dyspnea, appetite loss, tiredness, disorientation/confusion, and the SC Deteriorated Physical Condition/Decompensation of Home Care.
Conclusion: admissions to a SIPC ward are mainly caused by problems impairing mobility and autonomy. Results demonstrate that implementation of self- and reliability of proxy- and self-assessment is challenging, especially concerning non-physical symptoms/problems. We identified, specific symptoms and problems that might provide information needed for treatment discussions regarding the medical prognosis.
Objectives: To identify the types of factors included in research examining mortality in patients with dementia, and to stratify the identified factors by care settings.
Design: We systematically searched PubMed, Embase, PsycINFO and the Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases, and identified grey literature from the Networked Digital Library of Theses and Dissertations, Open Grey and Grey Literature Report. Two authors independently screened for eligibility of studies. Independent reviewers extracted relevant study information. We conducted a narrative synthesis of the data.
Results: We identified 8254 articles, of which 94 met the inclusion criteria. More than half (n=53) were published between 2009 and 2018 with half from Europe. Studies were conducted across hospices/nursing homes (n=25), hospital (n=23), outpatient clinics (n=21), mixed settings (n=15) and in the community (n=10). Nearly 60% adopted a prospective cohort study design with 87% performing multivariable analysis. Overall, 239 variables were identified and classified into six themes—individual factors, health status, functional ability, cognition and mental health, treatments and health system factors. Although a general set of factors were common across all studies, when stratified by care settings, variations were seen in the specific variables included.
Conclusion: Identifying prognostic variables relevant to the dementia population in each setting is key to facilitate appropriate care plans and to ensure timely access to palliative care options. Future research should also focus on ensuring the replicability of prognostic models and to generate a better understanding of the direct and interacting influence of the identified factors on mortality.
Introduction: Communication is considered a key skill for physicians globally and has formed a central part of medical curricula since the WHO identified it as a key attribute of the ‘5-star doctor’. Communication of poor prognosis to patients and caregivers is particularly challenging, yet an important example of physicians’ clinical communication, and a priority within palliative care research. Knowledge is scarce regarding the different positions physicians adopt during poor prognosis communication, especially in sub-Saharan countries.
Methods: This qualitative study took place at the Cape Coast Teaching Hospital in Ghana’s Central Region. Physicians in the internal medicine department, with experience in communicating poor prognosis to patients and families on a weekly basis were purposively sampled. Based on the concept of information power, a maximum variation of participants, in terms of age, sex, seniority and experience was achieved after conducting 10 semistructured interviews in March 2019. Positioning theory was used as a theoretical lens to inform study design. The data were analysed through a constructivist thematic analysis approach.
Results: Physicians adopted six positions, considered as six different themes, during their communication of poor prognosis: clinical expert, educator, counsellor, communicator, protector and mentor. Physicians’ choice of position was fluid, guided by local context and wider health system factors. Physicians’ desire to communicate with patients and families in a way that met their needs highlighted three key challenges for communication of poor prognosis: linguistic difficulties, pluralistic health beliefs and the role of family. These challenges presented ethical complexities in relation to autonomy and non-maleficence.
Conclusion: Context is key to physicians’ communication of poor prognosis. Communication of poor prognosis is multifaceted, complex and unpredictable. Physicians’ communication training should be developed to emphasise contextual circumstances and physician support, and international policy models on physicians’ roles developed to include a greater focus on social accountability.
ntroduction: Patients dying a short time after receiving palliative radiation are unlikely to have received benefit and may experience harm. To monitor the potential for avoidable harm, 30-day mortality following palliative radiation has been recommended for use as a quality indicator and the Royal College of Radiologist have recommended a rate of lower than 20%. At the Canterbury Regional Cancer and Haematology Service in Christchurch, New Zealand (CRCHS), we investigated 30-day mortality and evaluated the prognostic value of the TEACHH model in our population.
Methods: Palliative treatments from two, two-year periods (2012/2013 and 2016/2017) were retrospectively reviewed. We analysed 30-day mortality and several influencing variables. Patients were divided into three groups using the TEACHH model (type of cancer, performance status, age, prior palliative chemotherapy, prior hospitalizations and hepatic metastases).
Results: There were 1744 patients; 30-day mortality was 10% and was higher in patients with lung cancer (17% vs. 8% in non–lung cancer patients, P < 0.0001), patients having less than five fractions (13% vs. 9%, P : 0.0199) and patients in TEACHH group B/C (21% in C, 11% in B and 2% in group A, P < 0.0001). The majority of treatments (84%) used five fractions or less.
Conclusions: The mortality rate is within the suggested quality indicator, and the decreasing mortality with increasing fractionation demonstrates suitable selection of patients for longer treatment regimens. The TEACHH model can be used to increase precision in estimating prognosis, identifying patients who should not receive treatment and conversely identifying those for whom a prolonged fractionation schedule may be appropriate.
Background: the TEACHH and Chow models were developed to predict life expectancy (LE) in patients evaluated for palliative radiotherapy (PRT). We sought to validate the TEACHH and Chow models in patients who died within 90 days of PRT consultation.
Methods: A retrospective review was conducted on patients evaluated for PRT from 2017 to 2019 who died within 90 days of consultation. Data were collected for the TEACHH and Chow models; one point was assigned for each adverse factor. TEACHH model included: primary site of disease, ECOG performance status, age, prior palliative chemotherapy courses, hospitalization within the last 3 months, and presence of hepatic metastases; patients with 0-1, 2-4, and 5-6 adverse factors were categorized into groups (A, B, and C). The Chow model included non-breast primary, site of metastases other than bone only, and KPS; patients with 0-1, 2, or 3 adverse factors were categorized into groups (I, II, and III).
Results: A total of 505 patients with a median overall survival of 2.1 months (IQR: 0.7-2.6) were identified. Based on the TEACHH model, 10 (2.0%), 387 (76.6%), and 108 (21.4%) patients were predicted to live >1 year, >3 months to =1 year, and =3 months, respectively. Utilizing the Chow model, 108 (21.4%), 250 (49.5%), and 147 (29.1%) patients were expected to live 15.0, 6.5, and 2.3 months, respectively.
Conclusion: Neither the TEACHH nor Chow model correctly predict prognosis in a patient population with a survival <3 months. A better predictive tool is required to identify patients with short LE.
Aim: This study aims to analyze the prognostic value of seven tumor makers and also investigate the response of palliative chemotherapy in advanced NSCLC patients with advanced disease.
Methods: Medical records of 278 advanced NSCLC Chinese patients who received six cycles of palliative chemotherapy were retrospectively reviewed under ethical approval (JSCH2019K-011). Univariate and multivariate Cox regression analyses were performed using SPSS 24 to find the clinical value of these tumor markers and to identify the factors that were associated with progression-free survival (PFS), as well as the response to palliative chemotherapy.
Results: In baseline characteristic, the high levels of CEA, CA-125, CA-199, AFP, NSE, CYFRA21-1, and CA15-3 were detected in 209 (75.18%), 139 (50.0%), 62 (22.30%), 18 (6.47%), 155 (55.75%), 176 (63.30%), and 180 (64.74%) patients, respectively. Univariate analysis revealed that patients with high vs. normal levels of all tumor markers had an increased risk of poor prognosis. In the multivariable Cox regression model, the patient with (high vs. normal) CYFRA21-1 levels (HR = 1.454, P = 0.009) demonstrated an increased poor PFS. However, patients with (high vs. normal) CA19-9 levels (HR = 0.524, P < 0.0001) and NSE levels (HR = 0.584, P < 0.0001) presented a decreased risk of PFS. Also, patients receiving 3-drugs regimen had better PFS compared to those on 2-drugs regimen (P = 0.043).
Conclusions: The high levels of CYFRA21-1 was correlated with a poor prognostic factor of PFS for Advanced NSCLC patients. However, the high levels of CA19-9 and NSE were associated with a better prognostic factor of PFS. Additionally, smoking habits and tumor status had a poor prognostic factor of PFS. Moreover, we found that antiangiogenic therapy has high efficacy with first-line chemotherapy and longer PFS of NSCLC patients.
Objectives: To develop a mortality-predictive model for correct identification of patients with non-cancer multiple chronic conditions who would benefit from palliative care, recognise predictive indicators of death and provide with tools for individual risk score calculation.
Design: Retrospective observational study with multivariate logistic regression models.
Participants: All patients with high-risk multiple chronic conditions incorporated into an integrated care strategy that fulfil two conditions: (1) they belong to the top 5% of the programme’s risk pyramid according to the adjusted morbidity groups stratification tool and (2) they suffer simultaneously at least three selected chronic non-cancer pathologies (n=591).
Main outcome measure: 1 year mortality since patient inclusion in the programme.
Results: Among study participants, 201 (34%) died within the 1 year follow-up. Variables found to be independently associated to 1 year mortality were the Barthel Scale (p<0.001), creatinine value (p=0.032), existence of pressure ulcers (p=0.029) and patient global status (p<0.001). The area under the curve (AUC) for our model was 0.751, which was validated using bootstrapping (AUC=0.751) and k-fold cross-validation (10 folds; AUC=0.744). The Hosmer-Lemeshow test (p=0.761) showed good calibration.
Conclusions This study develops and validates a mortality prediction model that will guide transitions of care to non-cancer palliative care services. The model determines prognostic indicators of death and provides tools for the estimation of individual death risk scores for each patient. We present a nomogram, a graphical risk calculation instrument, that favours a practical and easy use of the model within clinical practices.
This issue of Medical Clinics, guest edited by Dr. Eric Widera, is devoted to Palliative Care. Articles in this important issue include: Hospice and palliative care: an overview; Goals of care conversations in palliative care: A practical guide; The art and science of prognostication in palliative care; Recognizing and managing polypharmacy in advanced illness; Pain management in those with serious illness; Management of grief, depression, and suicidal thoughts in those with serious illness; Management of respiratory symptoms in those with serious illness; Management of gastrointestinal symptoms inadvanced illness; Management of urgent medical conditions at the end of life; Delirium at the end of life; Options of last resort: palliative sedation, Physician aid in dying and voluntary cessation of eating and drinking; Cannabis for symptom management; and Self-care of physicians caring for patients with serious illness.
Context: Clinicians often worry that patients' recognition of the terminal nature of their illness may impair psychological well-being.
Objectives: To determine if such recognition was associated with decrements to psychological well-being that persisted over time.
Methods: About 87 patients with advanced cancer, with an oncologist-expected life expectancy of less than six months, were assessed before and after an oncology visit to discuss cancer restaging scan results and again at follow-up (median time between assessments, approximately six weeks). Prognostic understanding (PU) was assessed at previsit and postvisit, and a change score was computed. Psychological well-being was assessed at pre, post, and follow-up, and two change scores were computed (post minus pre; follow-up minus post).
Results: Changes toward more accurate PU was associated with a corresponding initial decline in psychological well-being (r = -0.33; P < 0.01) but thereafter was associated with subsequent improvements (r = 0.40; P < 0.001). This pattern remained controlling for potential confounds. Patients showed different patterns of psychological well-being change (F = 3.07, P = 0.05; F = 6.54, P < 0.01): among patients with improved PU accuracy, well-being initially decreased but subsequently recovered; by contrast, among patients with stable PU accuracy, well-being remained relatively unchanged, and among patients with decrements in PU accuracy, well-being initially improved but subsequently declined.
Conclusion: Improved PU may be associated with initial decrements in psychological well-being, followed by patients rebounding to baseline levels. Concerns about lasting psychological harm may not need to be a deterrent to having prognostic discussions with patients.
Context: Clinicians deciding whether to refer a patient or family to specialty palliative care report facing high levels of uncertainty. Most research on medical uncertainty has focused on prognostic uncertainty. As part of a pediatric palliative referral intervention for oncology teams we explored how uncertainty might influence palliative care referrals.
Objectives: To describe distinct meanings of the term “uncertainty” that emerged during the qualitative evaluation of the development and implementation of an intervention to help oncologists overcome barriers to palliative care referrals.
Methods: We conducted a phenomenological qualitative analysis of “uncertainty” as experienced and described by interdisciplinary pediatric oncology team members in discussions, group activities and semistructured interviews regarding the introduction of palliative care.
Results: We found that clinicians caring for patients with advanced cancer confront seven broad categories of uncertainty: prognostic, informational, individual, communication, relational, collegial, and inter-institutional. Each of these kinds of uncertainty can contribute to delays in referring patients to palliative care.
Conclusion: Various types of uncertainty arise in the care of pediatric patients with advanced cancer. To manage these forms of uncertainty, providers need to develop strategies and techniques to handle professionally challenging situations, communicate bad news, manage difficult interactions with families and colleagues, and collaborate with other organizations.
On March 28, 2020, the Office of Civil Rights at the Department of Health and Human Services (HHS) opened investigations into recently released critical care crisis triage protocols. Disability rights advocates are urging Congress to prohibit crisis triage based on “anticipated or demonstrated resource-intensity needs, the relative survival probabilities of patients deemed likely to benefit from medical treatment, and assessments of pre- or post-treatment quality of life.”
Acute-on-chronic liver failure (ACLF) occurs in about 25% of hospitalized patients with decompensated cirrhosis (DC) and is associated with high, short-term mortality . The European Association for the Study of the Liver (EASL) - Chronic Liver Failure (CLIF) EASL-CLIF Acute-on-Chronic Liver Failure in Cirrhosis (CANONIC) study showed that 28-day mortality could be predicted after the 3rd day in the intensive care unit (ICU) applying the CLIF-sequential organ failure assessment (SOFA) score.
OBJECTIVES: to establish the accuracy of community nurses' predictions of mortality among older people with multiple long-term conditions, to compare these with a mortality rating index and to assess the incremental value of nurses' predictions to the prognostic tool.
DESIGN: a prospective cohort study using questionnaires to gather clinical information about patients case managed by community nurses. Nurses estimated likelihood of mortality for each patient on a 5-point rating scale. The dataset was randomly split into derivation and validation cohorts. Cox proportional hazard models were used to estimate risk equations for the Revised Minimum Dataset Mortality Risk Index (MMRI-R) and nurses' predictions of mortality individually and combined. Measures of discrimination and calibration were calculated and compared within the validation cohort.
SETTING: two NHS Trusts in England providing case-management services by nurses for frail older people with multiple long-term conditions.
PARTICIPANTS: 867 patients on the caseload of 35 case-management nurses. 433 and 434 patients were assigned to the derivation and validation cohorts, respectively. Patients were followed up for 12 months.
RESULTS: 249 patients died (28.72%). In the validation cohort, MMRI-R demonstrated good discrimination (Harrell's c-index 0.71) and nurses' predictions similar discrimination (Harrell's c-index 0.70). There was no evidence of superiority in performance of either method individually (P = 0.83) but the MMRI-R and nurses' predictions together were superior to nurses' predictions alone (P = 0.01).
CONCLUSIONS: patient mortality is associated with higher MMRI-R scores and nurses' predictions of 12-month mortality. The MMRI-R enhanced nurses' predictions and may improve nurses' confidence in initiating anticipatory care interventions.
CONTEXT: Racial and ethnic disparities in end-of-life care are well documented among adults with advanced cancer.
OBJECTIVES: To examine the extent to which communication and care differ by race and ethnicity among children with advanced cancer.
METHODS: We conducted a prospective cohort study at 9 pediatric cancer centers enrolling 95 parents (42% racial/ethnic minorities) of children with poor prognosis cancer (relapsed/refractory high risk neuroblastoma). Parents were surveyed about whether prognosis was discussed; likelihood of cure; intent of current treatment; and primary goal of care. Medical records were used to identify higher intensity medical care since the most recent recurrence. Logistic regression evaluated differences between white non-Hispanic and minority (black, Hispanic, Asian/other race) parents.
RESULTS: 26% of parents recognized the child's low likelihood of cure. Minority parents were less likely to recognize the poor prognosis (OR .19, 95%CI .06-.63, P=.006) and the fact that current treatment was unlikely to offer cure (OR .07, 95%CI .02-.27, P<.0001). Children of minority parents were more likely to experience higher intensity medical care (OR 3.01, 95%CI 1.29-7.02, P=.01). After adjustment for understanding of prognosis, race/ethnicity was no longer associated with higher intensity medical care (aOR 2.14, 95%CI .84-5.46, P=.11), although power to detect an association was limited.
CONCLUSION: Parental understanding of prognosis is limited across racial and ethnic groups; racial and ethnic minorities are disproportionately affected. Perhaps as a result, minority children experience higher rates of high intensity medical care. Work to improve prognostic understanding should include focused work to meet needs of minority populations.
BACKGROUND: Emotional preparedness for death (hereafter called death preparedness) and prognostic awareness (PA), a distinct but related concept, each contributes to patients' practical, psychological, and interpersonal preparation for death. However, the distinction between these two concepts has never been investigated.
OBJECTIVE: To evaluate the distinction between death preparedness and accurate PA by examining their agreement over cancer patients' last year and the similarity of their predictors.
METHODS: For this secondary analysis of a longitudinal study of death preparedness for 277 cancer patients, agreement between death preparedness and accurate PA was evaluated by percentages and kappa coefficients, and predictors of the two outcomes were evaluated by multivariate logistic regression models with the generalized estimating equation.
RESULTS: Levels of agreement between reported death preparedness and accurate PA increased slightly (42.44%-52.85%) from 181-365 to 1-30 days before death, with kappa values from -0.190 (-0.319, -0.061) to -0.006 (-0.106, 0.093), indicating poor agreement. Participants who were male, older, reported financial sufficiency, had fewer distressing symptoms, and perceived higher levels of social support were more likely to report death preparedness. Participants who were female, had greater than high-school educational attainment, and endured higher levels of functional dependence were more likely to report accurate PA.
CONCLUSION: The distinction between death preparedness and accurate PA was supported by their poor agreement, lack of reciprocal associations, and two different sets of predictors. Healthcare professionals should not only cultivate cancer patients' accurate PA, but also facilitate emotional preparation for death to achieve a good death and improve end-of-life-care quality.
OPINION STATEMENT: Palliative care provides an extra layer of support to patients and families facing a serious illness. To date, several studies support the use of early, integrated palliative care for patients with cancer, based upon documented improvements in quality of life, symptoms, mood, satisfaction, utilization, and even overall survival. Despite this, patients with cancer continue to have unmet palliative care needs, and palliative care services are often engaged late in their care, if at all. Amid this under-utilization, questions remain about the optimal timing and nature of palliative care integration. To answer this question, we briefly review the evidence based for palliative care in oncology, and discuss three approaches to optimizing the timing of palliative care integration: (1) prognosis-based, (2) needs-based, and (3) trigger-based models. Prognosis-based models most closely mirror the approach of randomized trials to date, but are overly dependent on prognostication, and may miss patients with unmet needs who do not meet standard definitions of poor-prognosis disease. Needs-based models may better capture patients in a personalized manner, based on actual needs, but require sophisticated screening systems to be integrated into routine care processes, along with clinician buy-in. This may lead to excessive referrals, which strain the already limited palliative care workforce. As such, a blended, trigger-based approach may be best, allowing one to utilize certain disease-based and prognosis-based triggers for referral, plus screening of unmet needs, to identify those patients most likely to benefit from integrated palliative care when they need it most.
BACKGROUND: While prognostic information is considered important for treatment decision-making, physicians struggle to communicate prognosis to advanced cancer patients. This systematic review aimed to offer up-to-date, evidence-based guidance on prognostic communication in palliative oncology.
METHODS: PubMed and PsycInfo were searched until September 2019 for literature on the association between prognostic disclosure (strategies) and patient outcomes in palliative cancer care, and its moderators. Methodological quality was reported.
RESULTS: Eighteen studies were included. Concerning prognostic disclosure, results revealed a positive association with patients' prognostic awareness. Findings showed no or positive associations between prognostic disclosure and the physician-patient relationship or the discussion of care preferences. Evidence for an association with the documentation of care preferences or physical outcomes was lacking. Findings on the emotional consequences of prognostic disclosure were multifaceted. Concerning disclosure strategies, affective communication seemingly reduced patients' physiological arousal and improved perceived physician's support. Affective and explicit communication showed no or beneficial effects on patients' psychological well-being and satisfaction. Communicating multiple survival scenarios improved prognostic understanding. Physicians displaying expertise, positivity and collaboration fostered hope. Evidence on demographic, clinical and personality factors moderating the effect of prognostic communication was weak.
CONCLUSION: If preferred by patients, physicians could disclose prognosis using sensible strategies. The combination of explicit and affective communication, multiple survival scenarios and expert, positive, collaborative behaviour likely benefits most patients. Still, more evidence is needed, and tailoring communication to individual patients is warranted.
IMPLICATIONS: Future research should examine the effect of prognostic communication on psychological well-being over time and treatment decision-making, and focus on individualising care.
Prognostication is a vital aspect of decision making because it provides patients and families with information to establish realistic and achievable goals of care, is used in determining eligibility for certain benefits, and helps in targeting interventions to those likely to benefit. Prognostication consists of 3 components: clinicians use their clinical judgment or other tools to estimate the probability of an individual developing a particular outcome over a specific period of time; this prognostic estimate is communicated in accordance with the patient's information preferences; the prognostic estimate is interpreted by the patient or surrogate and used in clinical decision making.