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Sökning: onr:"swepub:oai:DiVA.org:uu-102492" > Proton therapy of c...

Proton therapy of cancer : potential clinical advantages and cost-effectiveness

Lundkvist, Jonas (författare)
Karolinska Institutet
Ekman, Mattias (författare)
Ericsson, Suzanne Rehn (författare)
Uppsala universitet,Institutionen för onkologi, radiologi och klinisk immunologi
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Jönsson, Bengt (författare)
Glimelius, Bengt (författare)
Karolinska Institutet,Uppsala universitet,Institutionen för onkologi, radiologi och klinisk immunologi
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 (creator_code:org_t)
2009-07-08
2005
Engelska.
Ingår i: Acta Oncologica. - : Informa UK Limited. - 0284-186X .- 1651-226X. ; 44:8, s. 850-61
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • Proton therapy may offer potential clinical advantages compared with conventional radiation therapy for many cancer patients. Due to the large investment costs for building a proton therapy facility, however, the treatment cost with proton radiation is higher than with conventional radiation. It is therefore important to evaluate whether the medical benefits of proton therapy are large enough to motivate the higher costs. We assessed the cost-effectiveness of proton therapy in the treatment of four different cancers: left-sided breast cancer, prostate cancer, head and neck cancer, and childhood medulloblastoma. A Markov cohort simulation model was created for each cancer type and used to simulate the life of patients treated with radiation. Cost and quality adjusted life years (QALYs) were used as primary outcome measures. The results indicated that proton therapy was cost-effective if appropriate risk groups were chosen. The average cost per QALY gained for the four types of cancer assessed was about pounds 10,130. If the value of a QALY was set to pounds 55,000, the total yearly net benefit of treating 925 cancer patients with the four types of cancer was about pounds 20.8 million. Investment in a proton facility may thus be cost-effective. The results must be interpreted with caution, since there is a lack of data, and consequently large uncertainties in the assumptions used.

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MEDICINE
MEDICIN

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