Literature DB >> 29112231

Individualized outcome prognostication for patients with laryngeal cancer.

Connor W Hoban1, Lauren J Beesley2, Emily L Bellile2, Yilun Sun2, Matthew E Spector1, Gregory T Wolf1, Jeremy M G Taylor2, Andrew G Shuman1.   

Abstract

BACKGROUND: Accurate prognostication is essential to the optimal management of laryngeal cancer. Predictive models have been developed to calculate the risk of oncologic outcomes, but extensive external validation of accuracy and reliability is necessary before implementing them into clinical practice.
METHOD: Four published prognostic calculators that predict 5-year overall survival for patients with laryngeal cancer were evaluated using patient information from a prospective epidemiology study cohort (n = 246; median follow-up, 60 months) with previously untreated, stage I through IVb laryngeal squamous cell carcinoma.
RESULTS: Different calculators yielded substantially different predictions for individual patients. The observed 5-year overall survival was significantly higher than the averaged predicted 5-year overall survival of the 4 calculators (71.9%; 95% confidence interval [CI], 65%-78%] vs 47.7%). Statistical analyses demonstrated the calculators' limited capacity to discriminate outcomes for risk-stratified patients. The area under the receiver operating characteristic curve ranged from 0.68 to 0.72. C-index values were similar for each of the 4 models (range, 0.66-0.68). There was a lower than expected hazard of death for patients who received induction (bioselective) chemotherapy (hazard ratio, 0.46; 95% CI, 0.24-0.88; P = .024) or primary surgical intervention (hazard ratio, 0.43; 95 % CI, 0.21-0.90; P = .024) compared with those who received concurrent chemoradiation.
CONCLUSIONS: Suboptimal reliability and accuracy limit the integration of existing individualized prediction tools into routine clinical decision making. The calculators predicted significantly worse than observed survival among patients who received induction chemotherapy and primary surgery, suggesting a need for updated consideration of modern treatment modalities. Further development of individualized prognostic calculators may improve risk prediction, treatment planning, and counseling for patients with laryngeal cancer. Cancer 2018;124:706-16.
© 2017 American Cancer Society. © 2017 American Cancer Society.

Entities:  

Keywords:  calculator; larynx cancer; nomogram; prognostication; risk prediction

Mesh:

Year:  2017        PMID: 29112231      PMCID: PMC5800991          DOI: 10.1002/cncr.31087

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  49 in total

1.  Hospital volume and surgical mortality in the United States.

Authors:  John D Birkmeyer; Andrea E Siewers; Emily V A Finlayson; Therese A Stukel; F Lee Lucas; Ida Batista; H Gilbert Welch; David E Wennberg
Journal:  N Engl J Med       Date:  2002-04-11       Impact factor: 91.245

Review 2.  Quality of care in head and neck cancer.

Authors:  Carol M Lewis; Randal S Weber; Ehab Y Hanna
Journal:  Curr Oncol Rep       Date:  2011-04       Impact factor: 5.075

3.  Individualized estimation of conditional survival for patients with head and neck cancer.

Authors:  Samuel J Wang; Amanda R Wissel; Celine B Ord; Jayashree Kalpathy-Cramer; C David Fuller; John M Holland; Neil D Gross
Journal:  Otolaryngol Head Neck Surg       Date:  2011-07       Impact factor: 3.497

4.  Development and validation of a nomogram for prediction of survival and local control in laryngeal carcinoma patients treated with radiotherapy alone: a cohort study based on 994 patients.

Authors:  Ada G T M Egelmeer; E Rios Velazquez; Jos M A de Jong; Cary Oberije; Yasmyne Geussens; Sandra Nuyts; Bernd Kremer; Derek Rietveld; C René Leemans; Monique C de Jong; Coen Rasch; Frank Hoebers; Jarrod Homer; Nick Slevin; Catharine West; Philippe Lambin
Journal:  Radiother Oncol       Date:  2011-07-23       Impact factor: 6.280

5.  Measuring the accuracy of prognostic judgments in oncology.

Authors:  W J Mackillop; C F Quirt
Journal:  J Clin Epidemiol       Date:  1997-01       Impact factor: 6.437

6.  Development and future of the American Society of Clinical Oncology's Quality Oncology Practice Initiative.

Authors:  Douglas W Blayney; Kristen McNiff; Peter D Eisenberg; Terry Gilmore; Paul B Jacobsen; Joseph O Jacobson; Pamela J Kadlubek; Michael N Neuss; Joseph Simone
Journal:  J Clin Oncol       Date:  2014-09-15       Impact factor: 44.544

Review 7.  Predicting cancer prognosis using interactive online tools: a systematic review and implications for cancer care providers.

Authors:  Borsika A Rabin; Bridget Gaglio; Tristan Sanders; Larissa Nekhlyudov; James W Dearing; Sheana Bull; Russell E Glasgow; Alfred Marcus
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2013-08-16       Impact factor: 4.254

Review 8.  Comparisons of nomograms and urologists' predictions in prostate cancer.

Authors:  Phillip L Ross; Claudia Gerigk; Mithat Gonen; Ofer Yossepowitch; Ilias Cagiannos; Pramod C Sogani; Peter T Scardino; Michael W Kattan
Journal:  Semin Urol Oncol       Date:  2002-05

9.  Biomarkers in advanced larynx cancer.

Authors:  Carol R Bradford; Bhavna Kumar; Emily Bellile; Julia Lee; Jeremy Taylor; Nisha D'Silva; Kitrina Cordell; Celina Kleer; Robbi Kupfer; Pawan Kumar; Susan Urba; Francis Worden; Avraham Eisbruch; Gregory T Wolf; Theodoros N Teknos; Mark E P Prince; Douglas B Chepeha; Norman D Hogikyan; Jeffrey S Moyer; Thomas E Carey
Journal:  Laryngoscope       Date:  2013-07-12       Impact factor: 3.325

Review 10.  External validation of multivariable prediction models: a systematic review of methodological conduct and reporting.

Authors:  Gary S Collins; Joris A de Groot; Susan Dutton; Omar Omar; Milensu Shanyinde; Abdelouahid Tajar; Merryn Voysey; Rose Wharton; Ly-Mee Yu; Karel G Moons; Douglas G Altman
Journal:  BMC Med Res Methodol       Date:  2014-03-19       Impact factor: 4.615

View more
  6 in total

1.  Identification and validation of methylation-driven genes prognostic signature for recurrence of laryngeal squamous cell carcinoma by integrated bioinformatics analysis.

Authors:  Jie Cui; Liping Wang; Waisheng Zhong; Zhen Chen; Jie Chen; Hong Yang; Genglong Liu
Journal:  Cancer Cell Int       Date:  2020-09-29       Impact factor: 5.722

2.  Individualized survival prediction for patients with oropharyngeal cancer in the human papillomavirus era.

Authors:  Lauren J Beesley; Peter G Hawkins; Lahin M Amlani; Emily L Bellile; Keith A Casper; Steven B Chinn; Avraham Eisbruch; Michelle L Mierzwa; Matthew E Spector; Gregory T Wolf; Andrew G Shuman; Jeremy M G Taylor
Journal:  Cancer       Date:  2018-10-06       Impact factor: 6.860

3.  Development of a Machine Learning Model for Survival Risk Stratification of Patients With Advanced Oral Cancer.

Authors:  Yi-Ju Tseng; Hsin-Yao Wang; Ting-Wei Lin; Jang-Jih Lu; Chia-Hsun Hsieh; Chun-Ta Liao
Journal:  JAMA Netw Open       Date:  2020-08-03

4.  Individualized prognostic calculators in the precision oncology era.

Authors:  Jeremy M G Taylor; Andrew G Shuman; Lauren J Beesley
Journal:  Oncotarget       Date:  2019-01-11

5.  Prognostic Nomogram for Early Gastric Cancer After Surgery to Assist Decision-Making for Treatment With Adjuvant Chemotherapy.

Authors:  Chao Zhang; Shutao Zhao; Xudong Wang
Journal:  Front Pharmacol       Date:  2022-04-08       Impact factor: 5.988

6.  Development and Assessment of a Model for Predicting Individualized Outcomes in Patients With Oropharyngeal Cancer.

Authors:  Lauren J Beesley; Andrew G Shuman; Michelle L Mierzwa; Emily L Bellile; Benjamin S Rosen; Keith A Casper; Mohannad Ibrahim; Sarah M Dermody; Gregory T Wolf; Steven B Chinn; Matthew E Spector; Robert J Baatenburg de Jong; Emilie A C Dronkers; Jeremy M G Taylor
Journal:  JAMA Netw Open       Date:  2021-08-02
  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.