title: Estimating hypoxic status in human tumors: a simulation using Eppendorf oxygen probe data in cervical cancer patients.
abstract: OBJECTIVE
  To define the minimal number of pO(2) measurements, with 90% sensitivity and 90% specificity, needed to categorize cervical tumors as either hypoxic or oxic.
  
  
  METHODS
  Using Eppendorf oxygen probe data from our ongoing prospective trial, we simulated the measurement of tumor oxygenation with a smaller number of data points in 135 patients with cervical cancer. The hypoxic proportion, defined as the percentage of pO(2) values <5 mm Hg (HP5), was calculated for each tumor. Hypoxic tumors were defined as those with a median HP5 >50%, and tumors with normal oxygen levels as those with a median HP5 < or =50%. A small number of pO(2) measurements were randomly selected from the Eppendorf measurements in each tumor, or per Eppendorf track, and used to define the tumor as hypoxic or oxic. The sensitivity and specificity were calculated, considering the classification as given by the complete set of Eppendorf measurements as the reference standard.
  
  
  RESULTS
  The probability of falsely classifying the tumor decreased as the selected number of pO(2) measurements per tumor increased, and at 16 measurements was approximately 10%. Adding additional measurements per tumor beyond 24 improved the ability to classify the tumor accurately only slightly. The probability of falsely classifying the tumor decreased as the pO(2) measurements per track increased. At five measurements per track, the probability of falsely classifying the tumor was approximately 9%.
  
  
  CONCLUSIONS
  Approximately 20 measurements per tumor, or five measurements per track, using the Eppendorf pO(2) histograph, are sufficient to categorize cervical tumors as hypoxic or oxic. The results of this study will serve as a guide for research clinicians in the use of this and other systems in the assessment of tumor oxygenation in humans.
authors.affiliation: Department of Radiation Oncology, Princess Margaret Hospital, University Health Network and University of Toronto, Toronto, Ontario, Canada.
authors.forename: Corinne M
authors.initials: CM
authors.lastname: Doll
authors.forename: Michael
authors.initials: M
authors.lastname: Milosevic
authors.forename: Melania
authors.initials: M
authors.lastname: Pintilie
authors.forename: Richard P
authors.initials: RP
authors.lastname: Hill
authors.forename: Anthony W
authors.initials: AW
authors.lastname: Fyles
mesh_terms: D000230:Adenocarcinoma / Q000737:chemistry / Q000378:metabolism / Q000401:mortality; D000328:Adult; D000368:Aged; D018196:Carcinoma, Adenosquamous / Q000737:chemistry / Q000378:metabolism / Q000401:mortality; D002294:Carcinoma, Squamous Cell / Q000737:chemistry / Q000378:metabolism / Q000401:mortality; D015687:Cell Hypoxia; D003198:Computer Simulation; D018572:Disease-Free Survival; D004566:Electrodes; D005188:False Negative Reactions; D005189:False Positive Reactions; D005260:Female; D006801:Humans; D008875:Middle Aged; D008954:Models, Biological; D010100:Oxygen / Q000032:analysis*; D010313:Partial Pressure; D011048:Polarography / Q000295:instrumentation*; D011237:Predictive Value of Tests; D011446:Prospective Studies; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D002583:Uterine Cervical Neoplasms / Q000737:chemistry / Q000378:metabolism* / Q000401:mortality
chemical_list: D010100:Oxygen