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1.
J Oncol Pract ; 13(5): e522-e529, 2017 05.
Article in English | MEDLINE | ID: mdl-28379722

ABSTRACT

PURPOSE: Via Pathways (clinical pathways for cancer) provide evidence-based guidance for specific patient presentations based on the merit of efficacy, then toxicity, and finally cost (if efficacy and toxicity are comparable). We evaluated the impact of a change to the guidance in the metastatic colorectal cancer (mCRC) setting across two large, integrated health networks. METHODS: Cetuximab and panitumumab were determined to have equal efficacy in the treatment of mCRC with no significant difference in toxicity based on recent data from key clinical studies. A cost analysis using Centers for Medicare and Medicaid Services average sales data determined a cost advantage for panitumumab. A substitution of panitumumab for cetuximab in the clinical pathway for all mCRC lines of therapy was initiated as of August 2014. RESULTS: In the preimplementation period, 86 (93.5%) and six (6.5%) treatment selections were for cetuximab and panitumumab, respectively. After the pathway change was implemented, 13 (18.1%) and 59 (81.9%) treatment selections were for cetuximab and panitumumab, respectively. The change in prescribing habits was rapidly altered by the pathway change. The estimated annualized cost savings for the two health networks resulting from the response to the pathway change was $711,021. CONCLUSION: This study demonstrates that clinical pathways can act as a tool to assist oncology practices in decreasing costs and quickly responding to changing treatment paradigms by providing clinicians with consensus-driven treatment recommendations that incorporate the most up-to-date clinical trial results, toxicity considerations, and regimen cost information.


Subject(s)
Colorectal Neoplasms/epidemiology , Critical Pathways , Adult , Aged , Aged, 80 and over , Antineoplastic Agents/therapeutic use , Clinical Decision-Making , Colorectal Neoplasms/pathology , Colorectal Neoplasms/therapy , Disease Management , Female , Health Care Costs , Humans , Male , Middle Aged , Molecular Targeted Therapy , Neoplasm Metastasis , Quality of Health Care
2.
J Oncol Pract ; 12(6): e681-7, 2016 06.
Article in English | MEDLINE | ID: mdl-27221995

ABSTRACT

PURPOSE: Breast cancer diagnostics have the ability to predict disease recurrence and the benefit of chemotherapy. This study measures the use of a diagnostic assay, Oncotype DX, when embedded in a breast cancer decision support algorithm and, on the basis of the assay results, the use of chemotherapy in the adjuvant setting. METHODS: UPMC CancerCenter retrospectively reviewed patients with estrogen receptor-positive, human epidermal growth factor receptor 2 (HER2)Neu-negative disease with zero to three positive nodes navigated in the Via Pathways decision support portal during a 12-month period. The breast algorithm prompted input of the assay recurrence score (RS) and then recommended hormonal therapy alone (HT) for low RS, or chemotherapy followed by HT for high RS. The patient's RS was correlated with the treatment decision. RESULTS: During this time period, 643 patients had ER-positive, HER2Neu-negative disease with zero to three positive nodes. Of those, 596 (92.7%) had diagnostic testing to determine chemotherapy plus HT versus HT alone, and 47 had chemotherapy followed by HT without an RS. For node-negative patients classified with low or high RS, pathway treatment adherence rates were 99.7% and 96.6%, respectively; node-positive patients had 95.7% and 87.5% adherence rates, respectively. CONCLUSION: This analysis demonstrates the use of a clinical pathway to measure the adoption of a diagnostic test, the Oncotype DX breast assay, and the use of the appropriate therapy on the basis of the RS. As more diagnostics are established to aid in the personalized treatment of diseases, pathways may be important in maintaining clinician awareness of the appropriate disease presentations where these tests should be used, measuring usage of these tests, and tracking the treatment decisions on the basis of test results.


Subject(s)
Breast Neoplasms/drug therapy , Decision Support Systems, Clinical , Adult , Aged , Aged, 80 and over , Algorithms , Biomarkers, Tumor/metabolism , Breast Neoplasms/diagnosis , Breast Neoplasms/metabolism , Chemotherapy, Adjuvant , Female , Humans , Middle Aged , Young Adult
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