| Title |
A new biologic prognostic model based on immunohistochemistry predicts survival in patients with diffuse large B-cell lymphoma
|
|---|---|
| Published in |
Blood, June 2012
|
| DOI | 10.1182/blood-2012-05-430389 |
| Pubmed ID | |
| Authors |
Anamarija M. Perry, Teresa M. Cardesa-Salzmann, Paul N. Meyer, Luis Colomo, Lynette M. Smith, Kai Fu, Timothy C. Greiner, Jan Delabie, Randy D. Gascoyne, Lisa Rimsza, Elaine S. Jaffe, German Ott, Andreas Rosenwald, Rita M. Braziel, Raymond Tubbs, James R. Cook, Louis M. Staudt, Joseph M. Connors, Laurie H. Sehn, Julie M. Vose, Armando López-Guillermo, Elias Campo, Wing C. Chan, Dennis D. Weisenburger |
| Abstract |
Biologic factors that predict the survival of patients with a diffuse large B-cell lymphoma, such as cell of origin and stromal signatures, have been discovered by gene expression profiling. We attempted to simulate these gene expression profiling findings and create a new biologic prognostic model based on immunohistochemistry. We studied 199 patients (125 in the training set, 74 in the validation set) with de novo diffuse large B-cell lymphoma treated with rituximab and CHOP (cyclophosphamide, doxorubicin, vincristine, and prednisone) or CHOP-like therapies, and immunohistochemical stains were performed on paraffin-embedded tissue microarrays. In the model, 1 point was awarded for each adverse prognostic factor: nongerminal center B cell-like subtype, SPARC (secreted protein, acidic, and rich in cysteine) < 5%, and microvascular density quartile 4. The model using these 3 biologic markers was highly predictive of overall survival and event-free survival in multivariate analysis after adjusting for the International Prognostic Index in both the training and validation sets. This new model delineates 2 groups of patients, 1 with a low biologic score (0-1) and good survival and the other with a high score (2-3) and poor survival. This new biologic prognostic model could be used with the International Prognostic Index to stratify patients for novel or risk-adapted therapies. |
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| France | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
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Mendeley demographics
Geographical breakdown
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|---|---|---|
| Japan | 1 | 1% |
| Italy | 1 | 1% |
| United Kingdom | 1 | 1% |
| Unknown | 75 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 19 | 24% |
| Student > Ph. D. Student | 11 | 14% |
| Other | 10 | 13% |
| Professor > Associate Professor | 8 | 10% |
| Student > Bachelor | 5 | 6% |
| Other | 16 | 21% |
| Unknown | 9 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 35 | 45% |
| Agricultural and Biological Sciences | 13 | 17% |
| Biochemistry, Genetics and Molecular Biology | 9 | 12% |
| Business, Management and Accounting | 1 | 1% |
| Computer Science | 1 | 1% |
| Other | 5 | 6% |
| Unknown | 14 | 18% |