DARWIN EU® Multiple myeloma: patient characterisation, treatments and survival in the period 2012-2022

04/07/2023
20/08/2026
EU PAS number:
EUPAS105033
Study
Finalised
Study type

Study topic

Human medicinal product

Study type

Non-interventional study

Scope of the study

Disease epidemiology
Drug utilisation
Effectiveness study (incl. comparative)

Data collection methods

Secondary use of data
Non-interventional study

Non-interventional study design

Cohort
Study drug and medical condition

Medicinal product name, other

Etidronate (ATC code: M05BA01), Etidronate (ATC code: L01XH03)

Study drug International non-proprietary name (INN) or common name

AXICABTAGENE CILOLEUCEL
BORTEZOMIB
BREXUCABTAGENE AUTOLEUCEL
CARFILZOMIB
CISPLATIN
CYCLOPHOSPHAMIDE
DARATUMUMAB
DENOSUMAB
DEXAMETHASONE
ELOTUZUMAB
IDECABTAGENE VICLEUCEL
ISATUXIMAB
LENALIDOMIDE
LISOCABTAGENE MARALEUCEL
POMALIDOMIDE
SELINEXOR
THALIDOMIDE
TISAGENLECLEUCEL
VENETOCLAX
ZOLEDRONIC ACID

Anatomical Therapeutic Chemical (ATC) code

(H02AB02) dexamethasone
dexamethasone
(H02AB07) prednisone
prednisone
(L01AA01) cyclophosphamide
cyclophosphamide
(L01AA03) melphalan
melphalan
(L01AA09) bendamustine
bendamustine
(L01CA02) vincristine
vincristine
(L01CB01) etoposide
etoposide
(L01DB01) doxorubicin
doxorubicin
(L01XA01) cisplatin
cisplatin
(L01XC23) elotuzumab
elotuzumab
(L01XC24) daratumumab
daratumumab
(L01XC38) isatuximab
isatuximab
(L01XG02) carfilzomib
carfilzomib
(L01XG03) ixazomib
ixazomib
(L01XL06) brexucabtagene autoleucel
brexucabtagene autoleucel
(L01XL07) idecabtagene vicleucel
idecabtagene vicleucel
(L01XL08) lisocabtagene maraleucel
lisocabtagene maraleucel
(L01XX32) bortezomib
bortezomib
(L01XX52) venetoclax
venetoclax
(L01XX66) selinexor
selinexor
(L01XX70) axicabtagene ciloleucel
axicabtagene ciloleucel
(L01XX71) tisagenlecleucel
tisagenlecleucel
(L04AX02) thalidomide
thalidomide
(L04AX04) lenalidomide
lenalidomide
(L04AX06) pomalidomide
pomalidomide
(M05BA02) clodronic acid
clodronic acid
(M05BA03) pamidronic acid
pamidronic acid
(M05BA06) ibandronic acid
ibandronic acid
(M05BA08) zoledronic acid
zoledronic acid
(M05BX04) denosumab
denosumab
(M05BA01) etidronic acid
etidronic acid

Medical condition to be studied

Plasma cell myeloma
Plasmacytoma

Additional medical condition(s)

Amyloid light chain amyloidosis due to multiple myeloma, Asymptomatic multiple myeloma, Bone marrow: myeloma cells, Extramedullary plasmacytoma, Hypogammaglobulinemia due to multiple myeloma, IgA myeloma, IgD myeloma, IgG myeloma, Indolent multiple myeloma, Kappa light chain myeloma, Lambda light chain myeloma, Light chain myeloma, Light chain nephropathy due to multiple myeloma, Multiple myeloma, Multiple myeloma in remission, Multiple solitary plasmacytomas, Myeloma-associated amyloidosis, Myeloma kidney, Neuropathy due to multiple myeloma, Non-secretory myeloma, Osteoporosis co-occurrent and due to multiple myeloma, Osteosclerotic myeloma, Plasma cell leukemia, Plasma cell leukemia in relapse, Plasma cell leukemia in remission, Primary cutaneous plasmacytoma, Relapse multiple myeloma, Smoldering myeloma, Solitary osseous myeloma
Population studied

Short description of the study population

The study population included all individuals identified in the contributing databases between 01/01/2012 and 31/12/2022 with a first diagnosis of multiple myeloma. Participants with a diagnosis of cancer (any, excluding non-melanoma skin cancer) any time prior to the diagnosis of multiple myeloma were excluded.

Age groups

  • Children (2 to < 12 years)
  • Adolescents (12 to < 18 years)
  • Adults (18 to < 46 years)
  • Adults (46 to < 65 years)
  • Adults (65 to < 75 years)
  • Adults (75 to < 85 years)
  • Adults (85 years and over)

Estimated number of subjects

20000000
Study design details

Study design

Population-based cohort study.

Main study objective

To characterise patients with multiple myeloma(MM) diagnosed 2012-2022. Specific objectives are to describe demographic and clinical characteristics of patients with MM at the time of diagnosis, MM treatments and MM treatment sequences and to estimate survival of incident MM cases during the study.

Setting

Inpatient and outpatient setting from 6 databases in 5 European countries.

Outcomes

Treatment/s initiated at index date, 1 to 30, 1 to 90 and/or 1 to 365 days post index date, and death.

Data analysis plan

Large-scale patient-level characterisation will be conducted. Age and sex at time of multiple myeloma diagnosis, medical history and medication use will be described. The number and % of patients receiving each of a pre-specified list of multiple myeloma treatments and treatment combinations will also be described. Additionally, treatment patterns and sequences over time will be described. Survival will be estimated as the probability of survival from any cause of death and will be reported using Kaplan-Meier plots. This analysis will be conducted only for databases with complete information on mortality. A minimum cell count of 5 will be used when reporting results, with any smaller counts obscured.

Summary results

CONCLUSION
In this study we provided a characterisation of 30,319 patients newly diagnosed with multiple myeloma in between 2012 and 2022 across Europe. The most frequent co-morbidities at and prior to the date of diagnoses were hypertension, renal impairment, hyperlipidemia, osteoarthritis, urinary tract infection, diabetes mellitus, and obesity, while the most frequent medications were drugs for acid related disorders, agents acting on the renin-angiotensin system, lipid modifying agents, opioids and psycholeptics.
Regarding multiple myeloma treatments, the most frequently used class of treatment in the year following diagnosis were glucocorticoids, followed by PIs, chemotherapies and IMiDs. Treatment sequences were described in CDWBordeaux, where the most common treatment sequences observed were only Melphalan, followed by Dexamethasone-Thalidomide-Bortezomib-Cyclophosphamide-Melphalan, Daratumumab, and Prednisone-Melphalan-Bortezomib. No difference in treatment was observed by sex, while IMiDs and PIs were consistently seen to be used less in older individuals.
The observed 5-year survival estimates were 0.49 (0.42 to 0.58) in IMASIS, 0.65 (0.64 to 0.66) in NCR, and 0.69 (0.67 to 0.7) in SIDIAP. Survival estimates were higher for CDWBordeaux and EBB, with 5-year survival estimated at 0.78 (0.75 to 0.81) and 0.76 (0.67 to 0.86). Survival probabilities were consistently similar by sex, but varied substantially by age groups, with a decrease in survival observed with older age.