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35 citation(s) found for "Jackson, Pamela".

Sex differences in GBM revealed by analysis of patient imaging, transcriptome, and survival data
Yang, Wei , Taylor, Sara , Whitmire, Paula , Singleton, Kyle , Wu, Ningying , Lathia, Justin D. , Berens, Michael E. , Barnholtz‐Sloan, Jill S. , Swanson, Kristin R. , Luo, Jingqin , Taylor, Sara J , Whitmire, Paula , Carrasco, Eduardo, Singleton, Kyle W , Lathia, Justin D , Berens, Michael E , Barnholtz-Sloan, Jill S , Swanson, Kristin R , Rubin, Joshua B , Warrington, Nicole M., Carrasco, Eduardo, Kim, Albert H. , Luo, Jingqin

Science Translational Medicine | January 2, 2019 | Volume: 11 | Issue: 473 | Pages: No page available

10.1126/scitranslmed.aao5253 | PMID 30602536 Get It

Male and female glioblastomas are biologically distinct, and improving outcomes may require sex-specific approaches to treatment.
TMOD-11. IMAGING BASED INVASION METRIC PREDICTIVE OF RESPONSE TO ABT414 IN ORTHOTOPIC EGFRviii AMPLIFIED PATIENT DERIVED XENOGRAFTS
Marin, Bianca M. , Paulson, Lisa, Kasle, Lauren, Jackson, Pamela , Marin, Bianca M , Massey, Susan Christine , Hawkins‐Daarud, Andrea , Mladek, Ann C. , Sarkaria, Jann N. , Swanson, Kristin R

Neuro-Oncology | November 5, 2018 | Volume: 20 | Issue: suppl_6 | Pages: vi270-vi271

10.1093/neuonc/noy148.1124 Get It

NIMG-12. RADIOGENOMICS ON VENUS AND MARS: IMPACT OF SEX-DIFFERENCES ON MRI AND GENETIC CORRELATIONS IN GLIOBLASTOMA
Hu, Leland , Gaw, Nathan , Yoon, Hyunsoo , Eschbacher, Jennifer , Smith, Kris A. , Karis, John P. , Whitmire, Paula , Singleton, Kyle , Jackson, Pamela , Bendok, Bernard R. , Mitchell, J. Ross , Li, Jing , Baxter, Leslie C. , Nakaji, Peter , Hawkins‐Daarud, Andrea , Massey, Susan Christine , Wu, Teresa , Tran, Nhan L. , Rubin, Joshua B , Swanson, Kristin R

Neuro-Oncology | November 5, 2018 | Volume: 20 | Issue: suppl_6 | Pages: vi178-vi178

10.1093/neuonc/noy148.739 Get It

TMOD-07. LOCALIZATION OF ERLOTONIB RELATIVE TO MRI-BASED TUMOR EXTENT IN PDX GLIOBLASTOMA MODEL: TOWARDS A MATHEMATICAL MODEL FOR THE INTERFACE BETWEEN MRI AND DRUG DISTRIBUTION
Jackson, Pamela , Ranjbar, Sara , Randall, Elizabeth C., Lopez, Begona, Hu, Leland , Regan, Michael S. , Abdelmoula, Walid M. , Lopez, Begona, Massey, Susan Christine , He, Lihong , Macura, Slobodan , Agar, Jeffrey N. , Sarkaria, Jann N. , Agar, Nathalie Y.R. , Swanson, Kristin R

Neuro-Oncology | November 5, 2018 | Volume: 20 | Issue: suppl_6 | Pages: vi269-vi270

10.1093/neuonc/noy148.1120 Get It

Distinct Phenotypic Clusters of Glioblastoma Growth and Response Kinetics Predict Survival
Rayfield, Corbin, Grady, Fillan S. , León, Gustavo De , Rockne, Russell C. , Jackson, Pamela , Vora, Mayur, Johnston, Sandra K. , Clark-Swanson, Kamala , Whitmire, Scott A., Gamez, Mauricio E. , Porter, Alyx B. , Hu, Leland , Gonzalez‐Cuyar, Luis F. , Vora, Sujay A., Swanson, Kristin R. , Rayfield, Corbin A, Grady, Fillan, De Leon, Gustavo, Rockne, Russell, Carrasco, Eduardo, Hawkins-Daarud, Andrea, Clark-Swanson, Kamala R., Whitmire, Scott, Porter, Alyx, Gonzalez-Cuyar, Luis, Vora, Sujay, Swanson, Kristin R , Carrasco, Eduardo , Hawkins‐Daarud, Andrea , Bendok, Bernard R.

JCO Clinical Cancer Informatics | March 1, 2018 | Volume: No volume available | Issue: 2 | Pages: 1-14

10.1200/cci.17.00080 | PMID 30652553 Get It

PurposeDespite the intra- and intertumoral heterogeneity seen in glioblastoma multiforme (GBM), there is little definitive data on the underlying cause of the differences in patient survivals. Serial imaging assessment of tumor growth allows quantification of tumor growth kinetics (TGK) measured in terms of changes in the velocity of radial expansion seen on imaging. Because a systematic study of this entire TGK phenotype—growth before treatment and during each treatment to recurrence —has never been coordinately studied in GBMs, we sought to identify whether patients cluster into discrete groups on the basis of their TGK.Patients and MethodsFrom our multi-institutional database, we identified 48 patients who underwent maximally safe resection followed by radiotherapy with imaging follow-up through the time of recurrence. The patients were then clustered into two groups through a k-means algorithm taking as input only the TGK before and during treatment.ResultsThere was a significant survival difference between the clusters ( P = .003). Paradoxically, patients among the long-lived cluster had significantly larger tumors at diagnosis ( P = .027) and faster growth before treatment ( P = .003) but demonstrated a better response to adjuvant chemotherapy ( P = .048). A predictive model was built to identify which cluster patients would likely fall into on the basis of information that would be available to clinicians immediately after radiotherapy (accuracy, 90.3%).ConclusionDichotomizing the heterogeneity of GBMs into two populations—one faster growing yet more responsive with increased survival and one slower growing yet less responsive with shorter survival—suggests that many patients who receive standard-of-care treatments may get better benefit from select alternative treatments.