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@ARTICLE{Hummel:291566,
      author       = {M. Hummel$^*$ and T. Hielscher$^*$ and M. Emde-Rajaratnam
                      and H. Salwender and S. Beck and C. Scheid and U. Bertsch
                      and H. Goldschmidt and A. Jauch and J. Moreaux and A.
                      Seckinger and D. Hose},
      title        = {{Q}uantitative {I}ntegrative {S}urvival {P}rediction in
                      {M}ultiple {M}yeloma {P}atients {T}reated {W}ith
                      {B}ortezomib-{B}ased {I}nduction, {H}igh-{D}ose {T}herapy
                      and {A}utologous {S}tem {C}ell {T}ransplantation.},
      journal      = {JCO precision oncology},
      volume       = {8},
      number       = {8},
      issn         = {2473-4284},
      address      = {Alexandria, VA},
      publisher    = {American Society of Clinical Oncology},
      reportid     = {DKFZ-2024-01451},
      pages        = {e2300613},
      year         = {2024},
      note         = {#EA:C060#},
      abstract     = {Given the high heterogeneity in survival for patients with
                      multiple myeloma, it would be clinically useful to
                      quantitatively predict the individual survival instead of
                      attributing patients to two to four risk groups as in
                      current models, for example, revised International Staging
                      System (R-ISS), R2-ISS, or Mayo-2022-score.Our aim was to
                      develop a quantitative prediction tool for individual
                      patient's 3-/5-year overall survival (OS) probability. We
                      integrated established clinical and molecular risk factors
                      into a comprehensive prognostic model and evaluated and
                      validated its risk discrimination capabilities versus R-ISS,
                      R2-ISS, and Mayo-2022-score.A nomogram for estimating OS
                      probabilities was built on the basis of a Cox regression
                      model. It allows one to translate the individual risk
                      profile of a patient into 3-/5-year OS probabilities by
                      attributing points to each prognostic factor and summing up
                      all points. The nomogram was externally validated regarding
                      discrimination and calibration. There was no obvious bias or
                      overfitting of the prognostic index on the validation
                      cohort. Resampling-based and external evaluation showed good
                      calibration. The c-index of the model was similar on the
                      training (0.76) and validation cohort (0.75) and
                      significantly higher than for the R-ISS (P < .001) or R2-ISS
                      (P < .01).In summary, we developed and validated individual
                      quantitative nomogram-based OS prediction. Continuous risk
                      assessment integrating molecular prognostic factors is
                      superior to R-ISS, R2-ISS, or Mayo-2022-score alone.},
      keywords     = {Multiple Myeloma: mortality / Multiple Myeloma: therapy /
                      Multiple Myeloma: drug therapy / Humans / Bortezomib:
                      therapeutic use / Male / Female / Middle Aged /
                      Transplantation, Autologous / Nomograms / Aged / Prognosis /
                      Hematopoietic Stem Cell Transplantation / Antineoplastic
                      Agents: therapeutic use / Induction Chemotherapy / Adult /
                      Survival Rate / Bortezomib (NLM Chemicals) / Antineoplastic
                      Agents (NLM Chemicals)},
      cin          = {C060},
      ddc          = {610},
      cid          = {I:(DE-He78)C060-20160331},
      pnm          = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
      pid          = {G:(DE-HGF)POF4-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:38986047},
      doi          = {10.1200/PO.23.00613},
      url          = {https://inrepo02.dkfz.de/record/291566},
}