HOMR model accurately predicts 1-year mortality in older … · Systematic Review of Prognostic...

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C U R T I N D , O ’ D O N N E L L D , D O Y L E D , G A L L A G H E R P , O ’ M A H O N Y D .

U N I V E R S I T Y C O L L E G E C O R K , I R E L A N D

E U G M S , S E P T E M B E R 2 1 , 2 0 1 7

HOMR model accurately predicts 1-year mortality in older

hospitalized patients

Background

George

Estimating prognosis

  doctors are inaccurate and overly optimistic

1.  Parkes CM. Accuracy of predictions of survival in later stages of cancer. BMJ 1972;ii: 29-31. [PMC free article][PubMed] 2.  Christakis N, Lamont E. Extent and determinants of error in doctors' prognoses. BMJ 2000;320: 469-73. [PMC free article][PubMed] 3.  Vigano A, Dorgan M, Buckingham J, Bruera E, Suarez-Alzamor ME. Survival prediction in terminal cancer patients: a systematic review of the

medical literature. Palliat Med 2000;14: 363-74. [PubMed] 4.  Christakis NA, Lamont ER. Extent and determinants of error in physicians' prognoses in terminally ill patients. West J Med. 2000 May; 172(5):

310–313.

Prediction Models

Prediction Models

Assessing Performance of Prediction models

  Discrimination (C Statistic)

  Calibration

  Transportability

Assessing Performance of Prediction models

  Discrimination (C Statistic)

  Calibration

  Transportability

Discrimination (C Statistic)

C statistic

≥0.9 Excellent

0.8 -0.89 Very good

0.7-0.79 Good

0.6-0.69 Fair

0.5-0.59 Poor

Discrimination (C Statistic)

C statistic

≥0.9 Excellent

0.8 -0.89 Very good

0.7-0.79 Good

0.6-0.69 Fair

0.5-0.59 Poor

Discrimination (C Statistic)

C statistic

≥0.9 Excellent

0.8 -0.89 Very good

0.7-0.79 Good

0.6-0.69 Fair

0.5-0.59 Poor

>

Assessing Performance of Prognostic models

  Discrimination (C Statistic)

  Calibration

  Transportability

Calibration

  Agreement between observed and predicted outcomes

  <10% difference indicates good calibration

Assessing Performance of Prognostic models

  Discrimination (C Statistic)

  Calibration

  Transportability

Transportability

  Different population

  Different location

  Different investigators

Systematic Review of Prognostic Models

  “testing of transportability was limited”

  “insufficient evidence at this time to recommend the widespread use..”

JAMA, 2012

The Hospital-patient One-year Mortality Risk (HOMR) Model (2014)

HOMR model

  Predicts 1 year mortality after hospitalization

  Cohort >3 million; Adults of all ages

  C statistic 0.9

  <1% difference between observed and expected mortality

HOMR model

HOMR model

HOMR score

Predicted risk

47 70%

46 63%

45 58%

44 53%

43 50%

42 46%

41 43%

40 37%

39 32%

Assessment of the performance of the HOMR model in an older Irish cohort

Methods

  Adult inpatients ≥65 under care of geriatric medicine service

  January 2013 –March 2015

  Primary outcome: death within 1 year after discharge from hospital

Results

Characteristic Male 43%

Mean age 82

Emergency admission 94%

Independent 67%

Home care 21.3%

Nursing home 7.7%

1409 patients

1150 alive

259 Dead

(18.4%)

Baseline

...........................................................................

1 year

Results

C statistic 0.79

(95% CI 0.75 -0.82)

Results

Calibration:

  Deaths: 259 (18.4%)

Results

Calibration:

  Deaths: 259 (18.4%)

  Predicted deaths 403 (28.8%)

Results

Calibration:

  Deaths: 259 (18.4%)

  Predicted deaths 403 (28.8%)

  Odds ratio for death: Irish population = North American population

Calibration

0

10

20

30

40

50

60

70

80

90

100

25 27 29 31 33 35 37 39 41 43 45 47 49 51

Predicted Observed

% dead at one year

HOMR score

Calibration

0

10

20

30

40

50

60

70

80

90

100

25 27 29 31 33 35 37 39 41 43 45 47 49 51

Predicted Observed

Medium risk

% dead at one year

HOMR score

Low risk

High risk

Re-calibration

0

10

20

30

40

50

60

70

80

90

100

25 27 29 31 33 35 37 39 41 43 45 47 49 51

Predicted Observed

% dead at one year

HOMR score

Discussion

Discussion

Model   Descrip-on  C-­‐Sta-s-c:  Deriva-on   Valida-on   Independent  valida-on  

HELP,  2000   Pa$ents  ≥80  years,  emergency  admissions  

C=  0.73  (N=1266)  

C=0.74  (N=150)  

-­‐  

Walter  et  al,  2001   Pa$ents  ≥70  years,  discharged  from  general  medicine  service  

C=0.75  (N=1495)  

C=0.79  (N=1427)  

C=0.72  (N=122;  pa$ents  ≥75;  5  year  mortality  predic$on  )  

BISEP,  2003   Pa$ents    ≥70  years,  admiJed  under  general  medicine  service  

C=0.83  (N=525)  

C=0.77  (N=1246)  

C=0.73    (N=122;  pa$ents  ≥75;  5  year  mortality  predic$on  )  

Levine  et  al,  2007   Pa$ents    ≥65  years  discharged  from  general  medicine  service  

C=0.67  (N=2739)  

C=0.65  (N=3643)   -­‐  

MPI,  2008  

Pa$ents    ≥65  years  admiJed  to  geriatric  unit  

C=0.75   C=0.75   -­‐  

Silver  Code,  2010   Pa$ents  ≥75    admiJed  through  the  emergency  department  

C=0.66  (N=5457)  

C=0.64  (N=5456)  

-­‐  

HOMR,  2014   Adult  pa$ents  admiJed  under  non-­‐psychiatric  hospital  services  

C=0.92  (N=319  531)  

C=0.89  -­‐0.92  (N=  2  862  996)  

C=0.79  (N=1409;  pa$ents  ≥65  years  discharged  from  geriatric  service)  

Discussion

Model   Descrip-on  C-­‐Sta-s-c:  Deriva-on   Valida-on   Independent  valida-on  

HELP,  2000   Pa$ents  ≥80  years,  emergency  admissions  

C=  0.73  (N=1266)  

C=0.74  (N=150)  

-­‐  

Walter  et  al,  2001   Pa$ents  ≥70  years,  discharged  from  general  medicine  service  

C=0.75  (N=1495)  

C=0.79  (N=1427)  

C=0.72  (N=122;  pa$ents  ≥75;  5  year  mortality  predic$on  )  

BISEP,  2003   Pa$ents    ≥70  years,  admiJed  under  general  medicine  service  

C=0.83  (N=525)  

C=0.77  (N=1246)  

C=0.73    (N=122;  pa$ents  ≥75;  5  year  mortality  predic$on  )  

Levine  et  al,  2007   Pa$ents    ≥65  years  discharged  from  general  medicine  service  

C=0.67  (N=2739)  

C=0.65  (N=3643)   -­‐  

MPI,  2008  

Pa$ents    ≥65  years  admiJed  to  geriatric  unit  

C=0.75   C=0.75   -­‐  

Silver  Code,  2010   Pa$ents  ≥75    admiJed  through  the  emergency  department  

C=0.66  (N=5457)  

C=0.64  (N=5456)  

-­‐  

HOMR,  2014   Adult  pa$ents  admiJed  under  non-­‐psychiatric  hospital  services  

C=0.92  (N=319  531)  

C=0.89  -­‐0.92  (N=  2  862  996)  

C=0.79  (N=1409;  pa$ents  ≥65  years  discharged  from  geriatric  service)  

Discussion

Model C statistic

HOMR 0.79

CHA2DS2-VASc 0.68

HAS-BLED 0.69

Discussion

Can the model be used to predict 1-year mortality in older hospitalized patients?

Conclusion

Conclusion

  Prognostic models are important

  HOMR model is robust

  Compares favourably to other prognostic models

  Re-calibrated model needs to be tested

Thank you

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