Readily available information could be edited, or further supplementary information could be provided if not all aspects are covered from available materials. This is likely to require an initial upfront cost to produce a document, after which printing costs per patient are likely to be small. The committee also acknowledged that discussions around whether ICDs remain an appropriate treatment option can require longer appointment times and often require re-visiting. However, the committee agreed that this is necessary to ensure the patient is well informed and to allow time for discussion. Around 5-10% of heart failure patients have ICDs, in which discussion about deactivation is only likely to be considered in a small proportion each year. Therefore, the committee did not consider that these recommendations would have a significant resource impact. Other considerations The committee noted that conversations around ICD deactivation, like other conversations around end of life, can be challenging for people and their families. Health care professionals should be aware that some people may require specialist psychological support or review. The committee acknowledged the Resuscitation Council (UK), the British Cardiovascular Society and the National Council for Palliative Care s guide for healthcare professionals regarding the deactivation of implantable cardioverter-defibrillators towards the end of life http://www.bhrs.com/files/files/Guidelines/CIEDs_Deactivation.pdf. The committee were reassured that the advice outlined in this document was in agreement with the recommendations they had made. 10.4 Identifying patients with an increased risk of mortality The disease trajectory for people with heart failure is difficult to predict, with episodes of stability punctuated by episodes of severe deterioration in symptoms within an overall decline over years. The uncertainty associated with length of life from diagnosis and often repeated episodes of severe deterioration can create anxiety for both patients and clinicians.


The uncertainty associated with length of life from diagnosis and often repeated episodes of severe deterioration can create anxiety for both patients and clinicians. This may prevent optimal advance care planning and targeting of therapies and resources to those who will benefit most. Consequently, there is increasing interest in prognostic tools to identify people who are entering the last year of life. Despite some prediction tools being widely available there are no national guidelines on their use. 10.4.2 Review question: In adults with heart failure, which validated risk tools best identify patients with heart failure who are at increased risk of mortality in the short term (up to 1 year)? For full details, see the review protocol in Appendix A. Table 150: PICO characteristics of review question Question In adults with heart failure, which validated risk tools best identify patients with heart failure who are at increased risk of mortality in the short term (up to 1 year)? Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Question In adults with heart failure, which validated risk tools best identify patients with heart failure who are at increased risk of mortality in the short term (up to 1 year)? Objective To determine which prognostic risk tools are the most accurate at predicting patient mortality, to support decisions about involvement of palliative care services and the use of palliative care processes. Population People with heart failure in a community or outpatient setting. Tools that are derived or validated in patients who are in an acute setting will also be included. The results will be stratified based on the setting in which the tools were validated in the study (admitted versus recently discharged versus community).


The results will be stratified based on the setting in which the tools were validated in the study (admitted versus recently discharged versus community). Risk tool Validated risk tools identified in the literature Target condition Mortality (all-cause at up to 1 year) Statistical outcomes Area under the ROC curve (AUC or c-statistic) Sensitivity, specificity, negative predictive value, positive predictive value Predicted risk versus observed risk (calibration) Other outcomes e.g., D statistic, R2 statistic and Brier score Reclassification Study types Prospective cohort studies Retrospective cohort studies will be included only if insufficient prospective cohort studies are identified Studies with less than 500 participants will be excluded. 10.4.3 Clinical evidence A search was conducted for prospective and retrospective cohorts assessing the prognostic accuracy of tools for assessing the risk of mortality at 1 year in people with heart failure. Fourteen studies The studies are summarised in Table 151, and the risk tools are summarised in Table 152 below. See also the study selection flow chart in Appendix C, coupled sensitivity and specificity forest plots in Appendix E, study evidence tables in Appendix F, and excluded studies list in Appendix I. Table 151: Summary of studies included in the review Study Risk tool Population Outcomes No of events (%) Study design Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Study Risk tool Population Outcomes No of events (%) Study design Allen Seattle Heart Failure Model MAGGIC project heart failure risk score Ambulatory people with heart failure, 21 years of age or older.


ISBN: 978-1-4731-3093-7 Study Risk tool Population Outcomes No of events (%) Study design Allen Seattle Heart Failure Model MAGGIC project heart failure risk score Ambulatory people with heart failure, 21 years of age or older. Age (mean SD) (years): 75.1 Male %: 52% Ejection fraction: Family origin not reported Setting: Multicentre Country: USA Follow-up: Not reported Participants recruited between Mortality at 1 year AUCSensitivit y Specificity PPV NPV Hosmer- Lemeshow test Mortality at 1 Retrospective cohort Franke nstein Untitled risk +NT-proBNP) People with heart failure due to left ventricular systolic dysfunction Male %: 76 Family origin not reported Setting: Castle Hill Hospital, Hull Country: UK Follow-up: median 32 months Participants recruited between November 2001 and October Mortality at 1 year AUC Mortality at 1 Retrospective cohort Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Study Risk tool Population Outcomes No of events (%) Study design Kanwa r HeartMate II Risk Score People with HF who received a continuous flow LVAD as the primary implant between 2010 and 2015 (INTERMACS registry). Age, years (mean (SD)): 57(13) Female %: 21 Family origin not reported Setting: Multicentre (over 150 hospitals) Country: United States Follow up: median 3.8 years Participants recruited between Mortality at 1 year AROC Mortality at 1 deaths) Retrospective cohort Kao Seattle Heart Failure Model People with heart failure due to left ventricular systolic dysfunction Male %: 76 Family origin not reported Setting: Castle Hill Hospital, Hull Country: UK Mean follow up not reported Participants were recruited previous to 2001 Mortality at 1 year AUC Predicted versus year mortality Mortality at 1 Retrospective analysis of RCT data Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights.


Age, years (mean (SD)): 57(13) Female %: 21 Family origin not reported Setting: Multicentre (over 150 hospitals) Country: United States Follow up: median 3.8 years Participants recruited between Mortality at 1 year AROC Mortality at 1 deaths) Retrospective cohort Kao Seattle Heart Failure Model People with heart failure due to left ventricular systolic dysfunction Male %: 76 Family origin not reported Setting: Castle Hill Hospital, Hull Country: UK Mean follow up not reported Participants were recruited previous to 2001 Mortality at 1 year AUC Predicted versus year mortality Mortality at 1 Retrospective analysis of RCT data Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Study Risk tool Population Outcomes No of events (%) Study design Ketchu m Seattle Heart Failure Model- D People with NHYA class II-III heart failure and impaired systolic function (ejection fraction 35%) who were on guideline recommended medical therapy. Age (years): 62 12 Male %: 80 Family origin not reported Setting: Multicentre Country: USA Mean follow-up of 21 months Participants were recruited between July 2005 and Mortality at 1 year AUC Predicted versus observed mortality at 1 year 101 deaths in a mean follow-up of Retrospective cohort Ky Seattle Heart Failure Model- D People with a clinical diagnosis of heart failure as determined by a heart failure specialist Male %: 66 Aetiology: Systolic heart failure: 86% Ischemic heart failure: 30% Family origin %: African American: 22 Setting: Multicentre Country: USA Follow up: Maximum of 5 years Recruitment period not reported Mortality at 1 year AUC Predicted versus observed mortality at 1 year over a maximum follow-up period of 5 years Retrospective cohort Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights.


Age (years): 62 12 Male %: 80 Family origin not reported Setting: Multicentre Country: USA Mean follow-up of 21 months Participants were recruited between July 2005 and Mortality at 1 year AUC Predicted versus observed mortality at 1 year 101 deaths in a mean follow-up of Retrospective cohort Ky Seattle Heart Failure Model- D People with a clinical diagnosis of heart failure as determined by a heart failure specialist Male %: 66 Aetiology: Systolic heart failure: 86% Ischemic heart failure: 30% Family origin %: African American: 22 Setting: Multicentre Country: USA Follow up: Maximum of 5 years Recruitment period not reported Mortality at 1 year AUC Predicted versus observed mortality at 1 year over a maximum follow-up period of 5 years Retrospective cohort Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Study Risk tool Population Outcomes No of events (%) Study design Lee Untitled risk score Newly admitted patients with a primary diagnosis of heart failure Female %: 50.5 Family origin: Not reported Setting: 14 hospitals Country: Canada Participants were recruited previous to 2001 Mortality at 1 year AUC Mortality at 1 Retrospective cohort Levy Seattle Heart Failure Model years and NYHA class II to IV heart failure Age (years): 71.7 7 Male %: 69 Family origin not reported Setting: Multicentre Country: 46 countries Follow-up not reported Participants were recruited previous to 2001 survival free from LVAD or transplantati on ROC Survival (free from LVAD or transplantati on) at 1 year: RENAISSANC Val-HeFT: IN-CHF: Retrospective analysis of cohort and RCT data RENAISSANCE People with EF 30% and NYHA class II to IV heart failure Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights.


ISBN: 978-1-4731-3093-7 Study Risk tool Population Outcomes No of events (%) Study design Lee Untitled risk score Newly admitted patients with a primary diagnosis of heart failure Female %: 50.5 Family origin: Not reported Setting: 14 hospitals Country: Canada Participants were recruited previous to 2001 Mortality at 1 year AUC Mortality at 1 Retrospective cohort Levy Seattle Heart Failure Model years and NYHA class II to IV heart failure Age (years): 71.7 7 Male %: 69 Family origin not reported Setting: Multicentre Country: 46 countries Follow-up not reported Participants were recruited previous to 2001 survival free from LVAD or transplantati on ROC Survival (free from LVAD or transplantati on) at 1 year: RENAISSANC Val-HeFT: IN-CHF: Retrospective analysis of cohort and RCT data RENAISSANCE People with EF 30% and NYHA class II to IV heart failure Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Study Risk tool Population Outcomes No of events (%) Study design Age (years): 62 12 Male %: 78 Family origin not reported Setting: Multicentre Country: USA and Canada Follow-up not reported Participants were recruited previous to 2001 Val-HeFT People with EF 40% and NYHA class II to IV heart failure Age (years): 63 11 Male %: 80 Family origin not reported Setting: Multicentre Country: 16 countries Follow-up not reported Participants were recruited previous to 2001 IN-CHF People with heart failure of any etiology, age, EF or comorbidity Age (years): 64 12 Male %: 76 Family origin not reported Setting: Multicentre Country: Italy Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights.


ISBN: 978-1-4731-3093-7 Study Risk tool Population Outcomes No of events (%) Study design Age (years): 62 12 Male %: 78 Family origin not reported Setting: Multicentre Country: USA and Canada Follow-up not reported Participants were recruited previous to 2001 Val-HeFT People with EF 40% and NYHA class II to IV heart failure Age (years): 63 11 Male %: 80 Family origin not reported Setting: Multicentre Country: 16 countries Follow-up not reported Participants were recruited previous to 2001 IN-CHF People with heart failure of any etiology, age, EF or comorbidity Age (years): 64 12 Male %: 76 Family origin not reported Setting: Multicentre Country: Italy Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Study Risk tool Population Outcomes No of events (%) Study design Follow-up not reported Participant recruitment period not reported May Seattle Heart Failure Model People with HF (defined as a decrease in left ventricular function characterized by an EF 40% or a physician- reported clinical HF diagnosis (i.e., American College of Cardiology/American Heart Association stage B/C) undergoing coronary angiography. Age (years): 67.0 (range 19-96) Male %: 61.4 Family origin not reported Setting: LDS Hospital (Salt Lake City, Utah) Country: USA Average follow-up (years): 4.4 Participants were recruited Mortality at 1 year AUC rate at 1 year The study reported the composite end point of death, transplantati on, and left ventricular assist device implantation. Over 90% of the overall events were mortality. Retrospective cohort Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights.


Retrospective cohort Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Study Risk tool Population Outcomes No of events (%) Study design Rector Untitled risk score (derived in Lee 2003) People admitted to the Minneapolis VA medical centre with a primary diagnosis of heart failure Age (years): 73 10 Male %: 98 Ischemic heart disease: 68% Family origin not reported Setting: Minneapolis VA Medical centre Country: Canada Follow-up period: 4.5 years Participants were recruited between January 1999 and Mortality at 1 year AUC Observed versus predicted mortality at 1 year mortality at 1 events) Retrospective cohort Regoli Seattle Heart Failure Model People who underwent CRT device implantation between January 2002 and January 2011 Age (years): 67.2 10.7 Male %: 77.4% Family origin not reported Setting: 5 centres Country: Europe (Italy, Switzerland and UK) Median follow-up of 40.1 months (IQR 25.2-60.0 months) Participants were recruited between January 2002 and Mortality at 1 year AUC-ROC during a median follow-up of Retrospective cohort Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Study Risk tool Population Outcomes No of events (%) Study design Sartipy MAGGIC project heart failure risk score People with clinician judged heart failure. Age (mean) (years): 75 Female %: 40 Heart failure with preserved EF NYHA class I or II: 57% NYHA class III: 38% NYHA class IV: 5% Family origin not reported Setting: Multicentre Country: Sweden Follow-up: mean 2.6 years Recruitment period is unclear Mortality at 1 year AROC Predicted versus year mortality mortality at 1 deaths) Retrospective cohort Senni People with a diagnosis of heart failure based on symptoms and signs of congestion and objective evidence of cardiac dysfunction at rest.


Age (mean) (years): 75 Female %: 40 Heart failure with preserved EF NYHA class I or II: 57% NYHA class III: 38% NYHA class IV: 5% Family origin not reported Setting: Multicentre Country: Sweden Follow-up: mean 2.6 years Recruitment period is unclear Mortality at 1 year AROC Predicted versus year mortality mortality at 1 deaths) Retrospective cohort Senni People with a diagnosis of heart failure based on symptoms and signs of congestion and objective evidence of cardiac dysfunction at rest. Age (median IQR) (years): 70 NYHA class III-IV: 33.6% Female %: 38.7 Family origin not reported Setting: Multicentre Country: Countries in Europe Follow-up not reported Participants were recruited Mortality at 1 year AUC Brier score mortality at 1 events) The study reported the composite end point of death and transplantati on. Over 90% of the overall events were mortality. Prospective and retrospective Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 Study Risk tool Population Outcomes No of events (%) Study design Spinar AHEAD tool n=6315 People with acute heart failure Age (mean) (years): 77 (52-91) Female %: 44.5 Family origin not reported Setting: Multicentre Country: Spain, France, Argentina, Finland, Switzerland, USA, Tunisia, Austria Follow-up not reported Participant recruitment period is unclear Mortality at 1 year AUC mortality at 1 deaths) Retrospective cohort Advanced heart failure and palliative care Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: Table 152: Summary of risk tools included in the review Risk tool Description of tool Comments Seattle Heart Failure Model Seattle Heart Failure Model-D Multivariate risk prediction model. The Seattle HF score is calculated by multiplying the coefficient by the variable and summing the values.


The Seattle HF score is calculated by multiplying the coefficient by the variable and summing the values. Variables included within the model are age (decade), gender (male), NYHA class,100/ejection fraction, ischemic etiology, systolic blood pressure, diuretic dose (mg/kg), allopurinol use, statin use, if sodium<138, 100/cholesterol (dL/mg), if haemoglobin more or less than 16, % lymphocytes and uric acid (mg/dL). The SHFM-D included the original SHFM variables, and the new variables of digoxin use, carvedilol use, and creatinine, with each individual s SHFM score derived as previously described. The SHFM has been updated on an iterative basis to incorporate new and relevant variables based on the publishing of various trials and guidelines. Specific information regarding these updates is available at https://depts.washington.edu/shfm/update.php Online calculator available at http://depts.washington.edu/shfm/ MAGGIC project heart failure risk score Risk factor Addition to risk score Advanced heart failure and palliative care Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: Risk tool Description of tool Comments Current smoker +1 Diagnosis of COPD +2 First diagnosis of heart failure in the past 18 months Not on beta-blocker +3 Not on ACEI/ARB +1 Online calculator available at http://www.heartfailurerisk.org/ Untitled risk tool (6MWT + NT-proBNP) Cut-off NT-proBNP (cut-off positive) Cut-off 6MWT (cut-off positive) cut-off: male, no BBL 650 pg/ml 396m Advanced heart failure and palliative care Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: Risk tool Description of tool Comments cut-off: male, BBL 743 pg/ml 368m cut-off: female, no BBL 714 pg/ml 270m cut-off: female, BBL 830 pg/ml 188m Patients were assigned 1-point if their 6MWT distance was below the prognostic threshold and one point if their NT-proBNP value was above the prognostic threshold.


ISBN: Risk tool Description of tool Comments cut-off: male, BBL 743 pg/ml 368m cut-off: female, no BBL 714 pg/ml 270m cut-off: female, BBL 830 pg/ml 188m Patients were assigned 1-point if their 6MWT distance was below the prognostic threshold and one point if their NT-proBNP value was above the prognostic threshold. Thus 3 risk-groups were identified One year mortality rates of patients: Group 1 (0 points): 2% risk of 1 year mortality Group 2 (1 point): 7% risk of 1 year mortality Group 3 (2 points): 14% risk of 1 year mortality AHEAD tool 1 point assigned for each age >70 years, diagnosis of atrial fibrillation, diagnosis of diabetes mellitus, creatinine > 130 mol/l, anaemia (M: 130, F: 120). Maximum score of 5. Each parameter was calculated as 1 point (maximum of 5 points) One year mortality rates of patients: The paper states that these % thresholds were calculated with an acceptable dose of simplificati on Advanced heart failure and palliative care Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: Risk tool Description of tool Comments HeartMate II Risk Score (HMRS) Calculation of HMRS: (0.0274 [age in years]) (0.723 [albumin g/dl]) (0.74 [creatinine mg/dl]) (1.136 [international normalized ratio (INR)]) (0.807 [centre LVAD volume 15*]). *Enter value of 1 if total centre LVAD volume is 15 and 0 if 15.


*Enter value of 1 if total centre LVAD volume is 15 and 0 if 15. One year survival rates of patients: Online calculator available at: http://www.pmidcalc.org/23265328 3C-HF score Dichotomized logistic regression model and corresponding points for the additive version of the 3C-HF score were calculated as follows: Variable Odds ratio Points (additive score) NYHA class III-IV vs I-II 4.09 13 No RAS inhibitors 2.01 8 Severe valve heart disease 2.02 7 No beta blocker 1.45 4 Chronic kidney dysfunction 1.79 6 Diabetes with target organ damage 1.62 6 Advanced heart failure and palliative care Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: Risk tool Description of tool Comments The study does not report % risk of mortality at one year for all of the 3C-HF risk score deciles. It reports a <1% risk of mortality for scores <5 and a 50% risk of mortality for scores 32. An online scoring system is available at http://www.3chf.org/site/index.php Untitled risk score Variable Points (additive score) Age +age (in years) Respiratory rate, min (minimal 20; + rate (in breaths/min) Systolic BP, mmHg 180: -50 Urea nitrogen (maximum, 60mg/dL) + level (in mg/dL) Sodium concentration <136 mEq/L +10 Advanced heart failure and palliative care Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights.


An online scoring system is available at http://www.3chf.org/site/index.php Untitled risk score Variable Points (additive score) Age +age (in years) Respiratory rate, min (minimal 20; + rate (in breaths/min) Systolic BP, mmHg 180: -50 Urea nitrogen (maximum, 60mg/dL) + level (in mg/dL) Sodium concentration <136 mEq/L +10 Advanced heart failure and palliative care Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: Risk tool Description of tool Comments Cerebrovascular disease +10 Hepatic cirrhosis +35 An electronic version of the risk scoring system is available at: http://www.ccort.ca/CHFriskmodel.asp 10.4.4 Discrimination and calibration Table 153: Clinical evidence profile: risk tools for predicting mortality (all-cause at up to 1 year) Risk tool No of studie s n Strata Risk of bias a Inconsistency b Indirectne ssc Imprecisi ond Sensitivi ty (%) Specifici ty (%) AUC(or C- statistic)/NPV/ PPV Calibration Quality Seattle Heart Failure Model study includ separa At threshold 50% predicted mortality Outpatien t mixed LO W No inconsistency No indirectne ss Not estimable HIGH At threshold 20% predicted mortality Advanced heart failure and palliative care Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights.


ISBN: Risk tool Description of tool Comments Cerebrovascular disease +10 Hepatic cirrhosis +35 An electronic version of the risk scoring system is available at: http://www.ccort.ca/CHFriskmodel.asp 10.4.4 Discrimination and calibration Table 153: Clinical evidence profile: risk tools for predicting mortality (all-cause at up to 1 year) Risk tool No of studie s n Strata Risk of bias a Inconsistency b Indirectne ssc Imprecisi ond Sensitivi ty (%) Specifici ty (%) AUC(or C- statistic)/NPV/ PPV Calibration Quality Seattle Heart Failure Model study includ separa At threshold 50% predicted mortality Outpatien t mixed LO W No inconsistency No indirectne ss Not estimable HIGH At threshold 20% predicted mortality Advanced heart failure and palliative care Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: Risk tool No of studie s n Strata Risk of bias a Inconsistency b Indirectne ssc Imprecisi ond Sensitivi ty (%) Specifici ty (%) AUC(or C- statistic)/NPV/ PPV Calibration Quality te cohort s) Outpatien t mixed LO W No inconsistency No indirectne ss Not estimable HIGH At any threshold Outpatien t mixed LO W Serious No indirectne ss Not estimable AUC: 0.66 Hosmer-Lemeshow: MODERA TE t mixed LO W Serious Unclear No imprecisio n : 0.99 LOW t mixed LO W Serious Unclear No imprecisio n t HFREF LO W Serious Serious Not estimable t HFREF LO W Serious No indirectne ss Not estimable MODERA TE t HFREF LO W Serious Serious No imprecisio n : 0.97 LOW t HFREF LO W Serious Serious No imprecisio n : 0.97 LOW t HFREF LO W Serious Serious No imprecisio n : 0.98 LOW Advanced heart failure and palliative care Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights.


ISBN: Risk tool No of studie s n Strata Risk of bias a Inconsistency b Indirectne ssc Imprecisi ond Sensitivi ty (%) Specifici ty (%) AUC(or C- statistic)/NPV/ PPV Calibration Quality te cohort s) Outpatien t mixed LO W No inconsistency No indirectne ss Not estimable HIGH At any threshold Outpatien t mixed LO W Serious No indirectne ss Not estimable AUC: 0.66 Hosmer-Lemeshow: MODERA TE t mixed LO W Serious Unclear No imprecisio n : 0.99 LOW t mixed LO W Serious Unclear No imprecisio n t HFREF LO W Serious Serious Not estimable t HFREF LO W Serious No indirectne ss Not estimable MODERA TE t HFREF LO W Serious Serious No imprecisio n : 0.97 LOW t HFREF LO W Serious Serious No imprecisio n : 0.97 LOW t HFREF LO W Serious Serious No imprecisio n : 0.98 LOW Advanced heart failure and palliative care Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: Risk tool No of studie s n Strata Risk of bias a Inconsistency b Indirectne ssc Imprecisi ond Sensitivi ty (%) Specifici ty (%) AUC(or C- statistic)/NPV/ PPV Calibration Quality hy LO W Serious Serious No imprecisio n : 0.99 LOW 1139 CRT LO W Serious No indirectne ss Not estimable AUC: 0.66 MODERA TE MAGGIC project heart failure risk score 2 At threshold 50% predicted mortality Outpatien t mixed HIG H No inconsistency No indirectne ss Not estimable MODERA TE At threshold 20% predicted mortality Outpatien t mixed HIG H No inconsistency No indirectne ss Not estimable MODERA TE At any threshold Outpatien t mixed HIG H Serious No indirectne ss Not estimable AUC: 0.69 Hosmer-Lemeshow: LOW Outpatien t mixed HIG H Serious Unclear Not estimable LOW Untitled risk tool + NT- proBNP) t HFREF HIG H No inconsistency No indirectne ss Not estimable AUC: 0.68 MODERA TE Advanced heart failure and palliative care Chronic Heart Failure NICE 2018.


ISBN: Risk tool No of studie s n Strata Risk of bias a Inconsistency b Indirectne ssc Imprecisi ond Sensitivi ty (%) Specifici ty (%) AUC(or C- statistic)/NPV/ PPV Calibration Quality hy LO W Serious Serious No imprecisio n : 0.99 LOW 1139 CRT LO W Serious No indirectne ss Not estimable AUC: 0.66 MODERA TE MAGGIC project heart failure risk score 2 At threshold 50% predicted mortality Outpatien t mixed HIG H No inconsistency No indirectne ss Not estimable MODERA TE At threshold 20% predicted mortality Outpatien t mixed HIG H No inconsistency No indirectne ss Not estimable MODERA TE At any threshold Outpatien t mixed HIG H Serious No indirectne ss Not estimable AUC: 0.69 Hosmer-Lemeshow: LOW Outpatien t mixed HIG H Serious Unclear Not estimable LOW Untitled risk tool + NT- proBNP) t HFREF HIG H No inconsistency No indirectne ss Not estimable AUC: 0.68 MODERA TE Advanced heart failure and palliative care Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights.


All rights reserved. Subject to Notice of rights. ISBN: Risk tool No of studie s n Strata Risk of bias a Inconsistency b Indirectne ssc Imprecisi ond Sensitivi ty (%) Specifici ty (%) AUC(or C- statistic)/NPV/ PPV Calibration Quality AHEAD tool Y HIG H No inconsistency Unclear Not estimable AUC: 0.63 VERY LOW HeartMa te II Risk Score LVAD HIG H No inconsistency No indirectne ss Not estimable AUC: 0.59 MODERA TE score t mixed LO W No inconsistency No indirectne ss No imprecisio n Brier score: 0.082 HIGH Untitled risk tool (Lee H No inconsistency Serious No imprecisio n Observed vs predicted mortality for the 5 risk scores categories: LOW 1407 Acute LO W No inconsistency Serious Not estimable AUC: 0.76 MODERA TE (a) Risk of bias was assessed using the PROBAST checklist items relating to risk of bias. (b) Inconsistency was assessed by inspecting the point estimate and confidence intervals of the sensitivity and specificity forest plots where this data was available, or the AUC where it was not. Particular attention was placed on the degree to which the confidence intervals overlapped. Whether the point estimate values were above or below 50% (diagnosis based on chance alone) and 70% (the threshold the committee set above which is acceptable to recommend a test) was also considered. Where there was little or no overlap between at least some of the confidence intervals and the values reported by the individual studies varied across 2 areas (for example, 50 70% and 70 100%) the Advanced heart failure and palliative care Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights.


Where there was little or no overlap between at least some of the confidence intervals and the values reported by the individual studies varied across 2 areas (for example, 50 70% and 70 100%) the Advanced heart failure and palliative care Chronic Heart Failure NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: evidence was downgraded by 1 increment, if the individual studies varied across 3 areas (for example, 0 50%, 50 70% and 70 100%) the evidence was downgraded by 2 increments. Where there was a significant degree of overlap in the confidence intervals little weight was placed on the variability of the point estimates above and below the 50% and 70% thresholds. (c) Indirectness was assessed using the PROBAST checklist items relating to applicability. (d) Imprecision was assessed according to the range of point estimates of the primary measure. The evidence was downgraded by 1 increment when there was more than 20% range of the confidence interval around the point estimate and downgraded by 2 increments when there was a range of more than 40%. Imprecision was not estimable where studies did not report confidence intervals. Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 10.4.5 Economic evidence Published literature No relevant health economic studies were identified. See also the health economic study selection flow chart in appendix D. 10.4.6 Evidence statements Clinical Evidence for 7 prognostic risk tools predicting mortality at 1 year were identified from 14 publications. The quality of the included evidence ranged from high to very low.


The quality of the included evidence ranged from high to very low. Evidence was downgraded for a number of reasons including indirectness of the population (as they were recruited previous to 2001 when the guidelines for CHF management were changed), risk of bias for reasons including a lack of calibration data, or inconsistency due to variability in discrimination statistics reported by the studies with a concomitant lack of overlap in the confidence intervals. A single high quality study (n=10,930) reported both the sensitivity and specificity of the SHFM at 50% and 20% mortality thresholds. At a mortality threshold of 50% the SHFM showed a very poor sensitivity of 0.05 and a good specificity of 0.99 and at the 20% threshold it showed a very poor sensitivity of 0.21 and a good specificity of 0.93. The same study reported the prognostic accuracy of the MAGGIC project heart failure risk score at these thresholds. It reported a very poor sensitivity of 0.3 and a good specificity of 0.99 at the 50% mortality threshold and a moderate sensitivity of 0.7 and moderate specificity of 0.61 at the 20% mortality threshold. Seven further studies ranging from moderate to low quality, reported AUC or c-statistics for the SHFM. The largest of the studies (n=10,930) reported a moderate c-statistic of 0.66. The remaining studies were considerably smaller (ranging in sample size from 872 to 5010) and were mostly rated as low quality. The discrimination statistics reported by these studies ranged from 0.66 to 0.76 with only a proportion of them reporting confidence intervals. Moderate quality evidence was found for a single study (n=676) reporting on an untitled risk tool which combined data from the 6MWT and NT-proBNP. This tool reported a moderate c-statistic of 0.68.


Moderate quality evidence was found for a single study (n=676) reporting on an untitled risk tool which combined data from the 6MWT and NT-proBNP. This tool reported a moderate c-statistic of 0.68. Moderate quality evidence was also found for a further 2 studies which reported on the Heartmate II risk score (n=11,523) and the 3C-HF score (n=4258). The Heartmate II risk score showed a moderate sensitivity of 0.59, while the 3C-HF tool reported a good c-statistic of 0.82 (0.81-0.83). Further moderate quality evidence was found for an untitled risk tool reported in 2 studies (n=2176). Both studies reported moderate discrimination statistics of 0.71 (0.67-0.76) and 0.76. A single very low quality study reported the prognostic accuracy of the AHEAD tool which reported a moderate c-statistic of 0.63. Although several of the studies met the minimum AUC threshold, only a single study reported the sensitivity and specificity of two tools at the relevant mortality thresholds of interest. These statistics provide more accurate insight into the ability of the tool to adequately stratify peoples risk of mortality at 1 year. Economic No relevant economic evaluations were identified. Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 10.4.7 Recommendations and link to evidence Recommendations Do not use prognostic risk tools to determine whether to refer a person with heart failure to palliative care services.


ISBN: 978-1-4731-3093-7 10.4.7 Recommendations and link to evidence Recommendations Do not use prognostic risk tools to determine whether to refer a person with heart failure to palliative care services. [2018] If the symptoms of a person with heart failure are worsening despite optimal specialist treatment, discuss their palliative care needs with the specialist heart failure MDT and consider a needs assessment for palliative Research recommendation What is the most accurate prognostic risk toos in predicting 1 year mortality from heart failure at specific clinically relevant thresholds (for example, sensitivity, specificity, negative predictive value and positive predictive value at a threshold of 50% risk of mortality at 1 year)? Relative values of different outcomes The committee were interested in which validated risk tools best identified patients with heart failure who are at increased risk of all-cause mortality in the short term (up to 1 year). The aim was to identify tools that may be used to support decisions about involvement of palliative care services and the use of palliative care processes. It was recognised that the risk of death was only one factor to consider in determining the need for palliative care services and processes, but that accurate prognostic tools would be of value in the identification and decision-making process. The committee did not intend that risk tools would be used to specifically estimate the number of years that a person may live, or as a criterion for palliative care referral. The committee agreed that all-cause mortality was the appropriate outcome, rather than heart failure or cardiovascular mortality, in the context of the broad objectives of this review question.


The committee agreed that all-cause mortality was the appropriate outcome, rather than heart failure or cardiovascular mortality, in the context of the broad objectives of this review question. The committee also agreed that the most relevant risk tools would be those that identified patients at increased risk of mortality at 1 year, as this was an appropriate time for putting in place supportive and palliative care processes if necessary. Risk tools that identified patients at high risk of death in the very short term (for example, in hospital, or within 30 or 60 days of discharge), or in the long term (for example 2, 5 or 10 years) were not considered appropriate for this review question as they would not necessarily capture the patients who might benefit from palliative care services and processes in a timely manner. Quality of the clinical evidence The review included 7 risk tools that were validated in a range of heart failure cohorts. Overall, the quality of the evidence ranged from very low to high, and varied significantly between the tools. Many of the studies included in the review reported the area under the curve (AUC) or c-statistic as the only accuracy data. The committee noted that this metric enabled comparison of the overall accuracy of the tools, and agreed a priori that a minimum AUC of 0.70 would be necessary to consider recommending a tool, but that AUC itself was unlikely to provide enough information to make a recommendation. For those tools where multiple studies reported the AUC in different cohorts, the results were inconsistent, with some studies suggesting an AUC of greater than 0.70, and others estimating a lower accuracy. Many studies also did not report calibration data and these were downgraded for risk of bias.


Many studies also did not report calibration data and these were downgraded for risk of bias. Some studies were also downgraded for indirectness as the patients in the cohorts were recruited prior to 2001, when best practice medical treatment for heart failure changed to include beta-blockers. This means that these data may not reflect accuracy of the tools in a population treated in Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 accordance with current usual care. The committee agreed that the most important accuracy data for establishing the utility of a risk tool was the sensitivity and specificity of the tool at clinically relevant thresholds (for example, at a threshold of 50% risk of mortality at 1 year). As the main aim of the tools was to identify patients who may benefit from a palliative care approach, sensitivity was agreed to be of great importance. However, depending on how the tool was used, high specificity was also crucial as wrongly categorising a person at high risk of death could have negative consequences for that person and their family. Only 1 study reported sensitivity and specificity data at specific thresholds (50% and 20% predicted mortality) for 2 tools (Seattle Heart Failure Model (SHFM) and the MAGGIC project heart failure risk score). The sensitivity and specificity data was graded high quality for the SHFM and moderate quality for the MAGGIC risk score (the latter was downgraded due to poor calibration and failure to recalibrate). Trade-off between clinical benefits and harms Overall, the committee were not persuaded that any of the risks tools included in the review identified patients with a high risk of mortality with sufficient accuracy to support their use.


Trade-off between clinical benefits and harms Overall, the committee were not persuaded that any of the risks tools included in the review identified patients with a high risk of mortality with sufficient accuracy to support their use. The SHFM was the most commonly reported tool included in the review. The estimated AUC for the SHFM ranged from 0.66 to 0.76 across the 10 cohort datasets. Because of this inconsistency, the committee could not be confident that the tool would meet its minimum threshold for AUC of 0.70. The data from 1 large cohort suggested an AUC of 0.66, but at the clinically relevant thresholds, the sensitivity of the tool was very low. Sensitivity was estimated at 0.5% for a threshold of 50% predicted mortality, and 20.7% at 20% predicted mortality. This meant that the vast majority of patients who died within a year had relatively low predicted mortality risks in other words, the tool failed to identify the patients who would die within the year. The committee agreed that a tool with such low sensitivity was therefore not helpful for identifying patients who may benefit from a more detailed palliative care assessment. In contrast, the specificity of the tool was high, 99.9% at the 50% predicted mortality threshold and 93.1% at the 20% predicted morality threshold. This suggested that at these thresholds, the tool was accurate at identifying patients who were less likely to die within the year. Based on this evidence, the committee discussed whether the tool could be used as a rule out tool, to identify those patients who were unlikely to need a palliative care needs assessment.


Based on this evidence, the committee discussed whether the tool could be used as a rule out tool, to identify those patients who were unlikely to need a palliative care needs assessment. However, the committee agreed that the main focus of the review was to positively identify patients who may benefit from palliative care services and processes, not to rule out patients, and decided that a recommendation to use the tool in this way would not be appropriate. The MAGGIC risk score was also reported in multiple studies, with an AUC ranging from 0.69 to 0.78. Again, the committee could not be sure that the tool would meet the minimum threshold for AUC of 0.70, especially when the confidence intervals around the AUC estimates were considered. Sensitivity and specificity data on this tool was available from the same large cohort mentioned above. Similarly to the SHFM, the sensitivity of the tool was very low (3.1%) and the specificity high (99.2%) at the clinically relevant threshold of 50% predicted mortality. Sensitivity at the threshold of 20% predicted mortality was somewhat higher (69.7%), indicating that at this threshold, the tool identified most of the patients who were at higher risk of death. However, at this threshold the MAGGIC score also labelled a Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 significant proportion of patients as at high risk of death who did not die within the year ( false positives ) (the specificity of the tool was only 61%). The MAGGIC data was also at high risk of bias due to poor calibration, suggesting that the absolute predicted risks from the tool did not align well with the observed risks in the population.


The MAGGIC data was also at high risk of bias due to poor calibration, suggesting that the absolute predicted risks from the tool did not align well with the observed risks in the population. Based on this data, the committee agreed that the MAGGIC tool would also not be an appropriate tool for positively identifying patients who may benefit from palliative care assessment. The remaining tools considered in the review were all only considered in single study cohorts, and none of them provided sensitivity or specificity data. The AUC for these tools ranged from 0.59 to 0.82. The committee discussed the 3C-HF tool, which was the only tool in the review with an AUC of above 0.80. The committee agreed that while the overall AUC was high, without data on the tool s performance at clinically relevant thresholds for identifying high risk patients (for example, the sensitivity and specificity of the tool at a threshold of 50% predicted mortality within 1 year), combined with the fact that the tool was only validated in a single study cohort, they would not be comfortable recommending the tool for assessing individual mortality risk. Overall, the committee agreed that the evidence did not support the use of any of the identified prognostic risk tools to identify heart failure patients at high risk of mortality. The committee also discussed the potential for serious harm from inappropriate use of risk tools in the palliative care context. Incorrectly categorising a person at high risk of death could have negative consequences for that person and their family. Further, if the tools were misused as a criterion for access to palliative care services that would also cause substantial harm, given they fail to identify many of the patients who may benefit from such interventions.


Further, if the tools were misused as a criterion for access to palliative care services that would also cause substantial harm, given they fail to identify many of the patients who may benefit from such interventions. The committee acknowledged that tools with a reasonably high AUC may be useful to establish risk at a population or cohort level, but they fail to demonstrate sufficient accuracy at the individual level. For those reasons, the committee agreed to make an explicit recommendation that the tools should not be used to determine whether to offer referral to palliative care services. The committee discussed that the trajectory of heart failure can be very unpredictable, especially in newly diagnosed patients and with the risk of sudden death, making prognostication is challenging in heart failure. This probably explained the poor performance of many of the identified risk tools. This uncertain trajectory makes identifying heart failure patients in need of palliative care services very difficult in clinical practice. The committee agreed that there are also inequalities issues across the country and potentially between different conditions in terms of access to palliative care services. This may partly stem from the particular challenges of prognostication in heart failure. In addition, the palliative care expert co- optee noted that people with heart failure sometimes see themselves as living with the condition rather than dying with it, and may be reluctant to access palliative care services because of the perception that they are for cancer patients. The committee discussed ways in which identification of heart failure patients in need of a specialist palliative care assessment could be improved, without the use of a formal risk tool. The committee discussed whether it would be possible to come up with an evidence-based list of markers that might trigger referral for specialist assessment.


The committee discussed whether it would be possible to come up with an evidence-based list of markers that might trigger referral for specialist assessment. However, the evidence Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 reviewed demonstrated that clinical markers, even when combined in a sophisticated, weighted risk tool algorithm, failed to accurately identify high risk patients at an individual level. Including a list of factors in the guideline would not only be challenging (how to select key factors from the many included in the various risk tools) but also risked misapplication in practice, particularly if the factors were not considered in the context of the individual patient and their overall health status. Rather than using risk tools or a list of factors, the committee agreed that the best approach was for healthcare professionals to discuss with the specialist MDT any person with heart failure whose condition is deteriorating over a period of time, and to consider a palliative care needs assessment in those people. The committee agreed that all HF services should have a process in place to identify patients who should be referred for a formal assessment of palliative care needs, and adjust their service configuration as appropriate to ensure this can occur. The committee also agreed that if palliative care processes or services were thought to be necessary, they should be implemented or engaged early, given the uncertainty of the prognosis for many patients with heart failure. The committee emphasised that involvement of palliative care services and use of palliative care processes includes a broad spectrum of interventions, and that different levels of care and support can be provided at various stages of the person s disease pathway.


The committee emphasised that involvement of palliative care services and use of palliative care processes includes a broad spectrum of interventions, and that different levels of care and support can be provided at various stages of the person s disease pathway. People should be reassured that use of palliative care processes does not necessarily mean referral to a hospice or the withdrawal of prognostic heart failure medication, and that people can dip in and out of palliative care over the course of their disease. The committee acknowledged that palliative care processes do not necessarily require delivery by specialist palliative care doctors and nurses. For example, GPs, geriatricians and heart failure specialist nurses may be specially trained to implement palliative care processes for heart failure patients. The committee agreed that people with heart failure and their family and carers should have access to professionals with palliative care skills within the specialist HF MDT, and all specialist HF MDTs should have access to specialist palliative care services and should involve those services where necessary. Future research The committee discussed the need for studies of prognostic risk tools in heart failure to report accuracy data (such as sensitivity, specificity and negative and positive predictive values) at specific clinically relevant thresholds, in order for the data to inform decisions about the value of the tools at an individual level in clinical practice. The committee decided that this was a priority for future research in this area and made a research recommendation to that effect. Trade-off between net clinical effects and costs No previously published economic evaluations were identified comparing different risk tools. The committee considered that the cost of using a risk tool would be minimal in the majority of cases and would only require a few minutes of a consultation.


The committee considered that the cost of using a risk tool would be minimal in the majority of cases and would only require a few minutes of a consultation. Some risk tools required the additional cost of blood tests, but these also incur a very small cost ( 1- 3). The committee considered that in most patients the last year of life is when a patient is most likely to benefit from palliative care services, and is when these services are likely to be most cost effective. However, as the accuracy Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 of the risk tools identified in the clinical review was too uncertain to predict the last year of life for heart failure patients, the committee were concerned about the potential large cost implications of flooding the palliative care services. Therefore, the committee agreed that it was important that if a clinician is concerned that a patient may require palliative services, that they discuss this with the specialist heart failure team for a second opinion and to check if there are any other treatments available that could be tried first which would not require palliative care services. The committee considered that this would only likely require a telephone call, email or letter and would therefore not incur significant resource. If it was still considered that the patient could possibly benefit from palliative care services, they should then be referred for a needs assessment by the palliative care team as they are best placed to determine whether palliative services are required.


If it was still considered that the patient could possibly benefit from palliative care services, they should then be referred for a needs assessment by the palliative care team as they are best placed to determine whether palliative services are required. The committee considered the resources required for this pathway of referral with regards to staff time, but agreed that this was most likely to be current practice and would therefore not have a significant resource impact. Other considerations The committee noted that health care professionals should also follow the related principles and recommendations in the NICE guidelines on Multimorbidity: clinical assessment and management (NG56), Care of dying adults in the last days of life (NG31) and End of life care for adults in the last year of life: service delivery when published (expected publication 2018). Chronic Heart Failure Advanced heart failure and palliative care NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 85.Do not offer long-term home oxygen therapy for advanced heart failure. Be aware that long-term home oxygen therapy may be offered for comorbidities, such as for some people with chronic obstructive pulmonary disease (see section 1.2.5 on oxygen in the NICE guidline on chronic obstructive pulmonary disease in over 16s. [2018] 86.If it is thought that a person may be entering the last 2 to 3 days of life, follow the NICE guideline on care of dying adults in the last days of life. [2018] See NICE s technology appraisal guidance on implantable cardioverter defibrillators and cardiac resynchronisation therapy for arrhythmias and heart failure.


[2018] See NICE s technology appraisal guidance on implantable cardioverter defibrillators and cardiac resynchronisation therapy for arrhythmias and heart failure. 87.When discussing implantation of a cardioverter defibrillator: explain the risks, benefits and consequences of cardioverter defibrillator implantation, following the principles on shared decision making in the NICE guideline on patient experience in adult NHS services ensure the person knows that the defibrillator can be deactivated without affecting any cardiac resynchronisation or pacing, and reactivated later explain the circumstances in which deactivation might be offered discuss and dispel common misconceptions about the function of the device and the consequences of deactivation provide the person and, if they wish, their family or carers with written information covering the information discussed. [2018] 88.Review the benefits and potential harms of a cardioverter defibrillator remaining active in a person with heart failure: at each 6-monthly review of their heart failure care whenever their care goals change as part of advance care planning if it is thought they are nearing the end of life. [2018] 89.Do not use prognostic risk tools to determine whether to refer a person with heart failure to palliative care services. [2018] 90.If the symptoms of a person with heart failure are worsening despite optimal specialist treatment, discuss their palliative care needs with the specialist heart failure MDT and consider a needs assessment for palliative care. [2018] 91.People with heart failure and their families or carers should have access to professionals with palliative care skills within the heart failure team. [2003] Chronic Heart Failure Reference list NICE 2018. All rights reserved. Subject to Notice of rights. ISBN: 978-1-4731-3093-7 11 Reference list 1. Abhayaratna WP, Marwick TH, Becker NG, Jeffery IM, McGill DA, Smith WT. Population- based detection of systolic and diastolic dysfunction with amino-terminal pro-B-type natriuretic peptide. American Heart Journal.


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