Do new cancer drugs offer good value for money? The perspectives of oncologists, health care policy makers, patients, and the general population

Figures & data

Table 1 Description of study participants

Characteristics	Oncologists (n=53)	Health care policy makers (n=25)	Patients (n=60)	General population (n=50)
Number contacted	425	140	210	420
Response rate (%)	12.5	17.9	28.6	11.9
Agreed to participate	53	25	60	50
Age (years ± SD)	46±9	43±11	49±9	37±10
Age (range)	27–66	26–58	29–71	21–63
Sex (female)	47%	56%	95%	52%

Abbreviation: SD, standard deviation.

Table 2 Scenario 1: minimum added survival that justifies an incremental cost of €50,000. Mean value expressed by type of participants and calculated ICER

Participants	Mean survival benefit (month ± SD)	ICER (€/QALY ± SD)
Oncologists	5.7±3.6	106,000±169,265
Health care policy makers	10.4±2.2	57,471±269,272
Patients	8.2±4.3	73,520±137,127
General population	9.1±4.1	66,074±145,123

Abbreviations: ICER, incremental cost-effectiveness ratio; SD, standard deviation; QALY, quality-adjusted life year.

Table 3 Scenario 2: accepted additional cost for a treatment that improves the QoL (40–80 in a 0–100 scale) twofold. Mean value expressed by the type of participants and by the calculated ICER

Participants	Mean additional cost (€ ± SD)	ICER (€/QALY ± SD)
Oncologists	26,000±18,876	65,000±47,190
Health care policy makers	17,040±12,016	42,600±30,039
Patients	33,167±20,589	82,917±51,472
General population	30,200±20,652	75,500±51,629

Abbreviations: QoL, quality of life; ICER, incremental cost-effectiveness ratio; SD, standard deviation; QALY, quality-adjusted life year.