Development of the ProPal-COPD tool to identify patients with COPD for proactive palliative care

Figures & data

Table 1 Set of 11 predictors of poor prognosis for patients hospitalized for an AECOPD and the references with the rational to include them in the prediction model

Predictors of poor prognosis	References
1. Hypoxemia (PaO2 <8 kPa) or hypercapnia (PaCO2 >6 kPa) at discharge	^Citation16,Citation17
2. Treatment of the exacerbation with NIV	^Citation21
3. Patient needs professional home care service for personal care after discharge	^Citation22
4. Negative answer to the surprise question: “Would I (as pulmonologist) be surprised if this patient would die in the next year?”	^Citation23
5. The diagnosis of a severe comorbidity such as:
a. Non-curable malignancy or	^Citation17,Citation24
b. Cor pulmonale (proven or non-proven) or	^Citation16
c. Proven CHF or	^Citation16,Citation17
d. Diabetes mellitus with neuropathy or	^Citation16,Citation17
e. Renal failure, clearance <40 (GFR, mL/min)	^Citation16,Citation17
6. CCQ total, day version >3	^Citation25
7. MRC dyspnea =5	^Citation16,Citation26
8. FEV1 (measured before AECOPD) <30% of predicted	^Citation16,Citation17
9. BMI <21 or unplanned weight loss (>10% in the last 6 months or >5% in last month)	^Citation16,Citation17
10. Previous hospital admissions for AECOPD (last 2 years ≥2 and/or last year ≥1)	^Citation16
11. Age >70 years	^Citation16,Citation17

Notes: PaCO₂, arterial partial pressure of carbon dioxide; PaO₂, arterial partial pressure of oxygen.

Abbreviations: AECOPD, acute exacerbation COPD; BMI, body mass index; CCQ, Clinical COPD Questionnaire; CHF, chronic heart failure; FEV₁, forced expiratory volume in 1 second; GFR, glomerular filtration rate; MRC dyspnea, Medical Research Council dyspnea questionnaire; NIV, noninvasive ventilation.

Table 2 Characteristics of the study population

Characteristics	Mean	±SD
Age, years	67.5	±9.6
Pack years	36.4	±32.8
	n	%
Sex
Male	68	43.9
Marital status*
Married	110	71.0
Unmarried	11	7.1
Divorced	13	8.4
Widow	18	11.6
Condition of living*
Single	34	21.9
Non-single	111	71.6
Place of living*
Home, independent of home care	103	66.5
Home, dependent of home care	45	29.0
Residential home	2	1.3
Highest level of education*
No education	1	0.6
Elementary school	21	13.5
Secondary school	47	30.3
Primary education	35	22.6
Secondary education	29	18.7
Higher/university education	15	9.7
GOLD stage*,•
0	8	5.2
I	10	6.5
II	41	26.5
III	52	33.5
IV	36	23.2
Predictors
Hypoxemia or hypercapnia	62	40.0
NIV	11	7.1
Professional home care	50	32.3
Negative answer SQ	76	49.0
Comorbidity	31	20.0
CCQ total, day version >3	96	61.9
MRC dyspnea =5	71	45.8
FEV1 <30% of predicted	45	29.0
BMI <21 or weight loss	26	16.8
Prev hosp AECOPD	62	40.0
Age >70 years	62	40.0

Notes: Study population (N=155).

* Because of missing values, some numbers do not add up to 100%.

• GOLD stage according to the last known data in medical file; inclusion in the study was based on the judgment by pulmonologist.

Abbreviations: AECOPD, acute exacerbation COPD; BMI, body mass index; CCQ, Clinical COPD Questionnaire; FEV₁, forced expiratory volume in 1 second; GOLD, Global Initiative for Chronic Obstructive Lung Disease; MRC dyspnea, Medical Research Council dyspnea questionnaire; NIV, noninvasive ventilation; prev hosp, previous hospitalization; SQ, surprise question.

Figure 1 Participant flow diagram.

Abbreviation: Pt, patient.

Table 3 The discriminating power of individual predictors in predicting death within 1 year

Predictor	Se	Sp	AUC
Hypoxemia or hypercapnia	0.53	0.63	0.583
NIV	0.93	0.07	0.503
Professional home care	0.47	0.71	0.589
Negative answer SQ	0.80	0.58	0.692
Comorbidity	0.43	0.86	0.645
CCQ total, day version >3	0.83	0.43	0.633
MRC dyspnea =5	0.80	0.62	0.712
FEV1 <30% of predicted	0.43	0.64	0.589
BMI <21 or weight loss	0.33	0.87	0.603
Previous hospitalization AECOPD	0.60	0.65	0.624
Age >70 years	0.43	0.61	0.521

Note: Study population (N=155).

Abbreviations: AECOPD, acute exacerbation COPD; AUC, area under the curve; BMI, body mass index; CCQ, Clinical COPD Questionnaire; FEV₁, forced expiratory volume in 1 second; MRC dyspnea, Medical Research Council dyspnea questionnaire; NIV, noninvasive ventilation; Se, sensitivity; Sp, specificity; SQ, surprise question.

Table 4 Optimal prediction model and its predictive performance of death within 1 year

Predictors in model	B	AUC	True AUC	95% CI
Intercept	−3.901	0.870	0.818	0.813–0.824
Hypoxemia or hypercapnia	/
NIV	/
Professional home care	/
Negative answer SQ	0.959
Comorbidity	1.479
CCQ total, day version >3	0.257
MRC dyspnea =5	1.475
FEV1 <30% of predicted	0.565
BMI <21 or weight loss	1.005
Prev hosp AECOPD	0.102
Age >70 years	/

Notes: Study population (N=155). B, weight in the model./, not incorporated in the optimal prediction model.

Abbreviations: AECOPD, acute exacerbation COPD; AUC, area under the curve; BMI, body mass index; CCQ, Clinical COPD Questionnaire; CI, confidence interval; FEV₁, forced expiratory volume in 1 second; MRC dyspnea, Medical Research Council dyspnea questionnaire; NIV, noninvasive ventilation; prev hosp, previous hospitalization; SQ, surprise question.

Table 5 Possible cutoffs considering different trade-offs between Se and Sp of the optimal prediction model

Cutoff	Se	Sp	Se + Sp	1.5 Se + Sp
−1.105	0.800	0.840	1.640	2.040
−2.896	0.967	0.328	1.295	1.778
−2.169	0.933	0.504	1.437	1.904
−1.362	0.900	0.728	1.628	2.078

Abbreviations: Se, sensitivity; Sp, specificity.

Figure 2 The ROC curve for the prediction of death within 1 year with the optimal cutoffs considering different trade-offs between Se and Sp.

Abbreviations: ROC, receiver operating characteristic; Se, sensitivity; Sp, specificity.

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