Prognostic implications of cytogenetics in adults with acute lymphoblastic leukemia treated with inotuzumab ozogamicin.
Elias J JabbourAnjali S AdvaniMatthias StelljesWendy StockMichaela LiedtkeNicola GökbugetGiovanni MartinelliSusan M O'BrienJane Liang WhiteTao WangM Luisa PaccagnellaBarbara SleightErik VandendriesDaniel J DeAngeloHagop M KantarjianPublished in: American journal of hematology (2019)
Karyotype is frequently used to predict response and outcome in leukemia. This post hoc exploratory analysis evaluated the relationship between baseline cytogenetics and outcome in patients with relapsed/refractory acute lymphoblastic leukemia (R/R ALL) treated with inotuzumab ozogamicin (InO), a humanized CD22 antibody conjugated to calicheamicin, in the phase 3, open-label, randomized INO-VATE trial. Data as of March 8, 2016, are presented in this analysis. Of the 326 patients randomized, 284 had screening karyotyping data (144 in the InO arm and 140 in the standard care [SC] arm). With InO, complete remission or complete remission with incomplete hematologic recovery (CR/CRi), minimal residual disease negativity rates, and overall survival (OS) were not significantly different between cytogenetic subgroups. CR/CRi rates favored InO over SC in the diploid with ≥20 metaphases, complex, and "other" cytogenetic subgroups. The OS hazard ratio favored InO over SC in the diploid with ≥20 metaphases, complex, and other cytogenetic subgroups. Generally, InO is effective and provides substantial clinical benefit in patients with R/R ALL who have specific baseline karyotypes.
Keyphrases
- acute lymphoblastic leukemia
- open label
- phase iii
- phase ii
- allogeneic hematopoietic stem cell transplantation
- newly diagnosed
- double blind
- clinical trial
- end stage renal disease
- healthcare
- placebo controlled
- electronic health record
- acute myeloid leukemia
- ejection fraction
- phase ii study
- chronic kidney disease
- palliative care
- randomized controlled trial
- ulcerative colitis
- photodynamic therapy
- prognostic factors
- chronic pain
- pain management
- systemic lupus erythematosus
- radiation therapy
- deep learning
- data analysis
- health insurance