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Cervical Cancer Case Study. Supervising Professor: Dr. P.D.M. Macdonald Team Members: Christine Calzonetti, Simo Goshev, Rongfang Gu, Shahidul Mohammad Islam, Amanda Lafontaine, Marcus Loreti, Maria Porco, William Volterman, Qihao Xie.

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slide1

Cervical Cancer Case Study

Supervising Professor: Dr. P.D.M. Macdonald

Team Members: Christine Calzonetti, Simo Goshev, Rongfang Gu, Shahidul Mohammad Islam, Amanda Lafontaine, Marcus Loreti, Maria Porco, William Volterman, Qihao Xie

-McMaster University-

slide2

Objectives:

  • To determine which of the documented variables are useful for predicting recurrence of the disease
  • To evaluate the extent to which tumor size, in particular, predicts the recurrence of the disease
slide4

Mean

Median

Standard deviation

Non-relapse

42.08

40

11.04

Relapse

42.04

39

11.17

  • The majority of patients observed were between the ages of 35 and 50
  • No significant difference between relapse and non-relapse patients
slide5

Mean

Median

Standard deviation

Non-relapse

6.76

5

6.83

Relapse

7.71

11

10.11

  • Similar means
  • Dissimilar boxplots possibly due to outliers
  • Missing values in the relapse group may have affected the outcome
slide6

Mean

Median

Standard deviation

Non-relapse

8.07

0

10.17

Relapse

18.86

20

16.31

  • A great disparity exists between the means and variability of relapse and non-relapse patients
  • Relapse patients had larger tumor sizes upon diagnosis, suggesting that tumor size should be considered an important prognostic factor
slide7

The difference in pie charts indicates that there are more cancerous cells found in the lymph nodes of patients who relapsed

  • The statistical significance is unclear
slide9

Recorded at the time of follow up appointment (therefore cannot be used as a diagnostic factor)

  • Most non-relapse patients have no presence of disease at last follow up appointment
  • In relapse patients, approx. ½ died of disease, ¼ are alive with disease, ¼ are alive with no evidence of disease
slide10

Results and

Conclusions

slide11

Survival Plot of Cervical Cancer Data

  • Survival plot of data indicates that most relapses occur during the first three years after surgery, it is highly unlikely that relapse will occur after eight years
  • The exponential curve deviated away from the survival curve at the tail end due to the patients who will never relapse
slide13

Small (0-10mm)

Medium (11-30mm)

Large (30+mm)

Time

  • Recurrence time for large group considerably lower than medium
  • Clear distinction between medium and small
  • The patients in the different size groups had noticeably different mean times to recur
slide15

Survival Analysis yielded the following results:

  • Significant difference between medium and small groups
  • Significant difference between large and small groups
  • Same results found using Weibull distribution in place of exponential distribution

A survival analysis of the data on S-Plus where the exponential distribution was assumed produced the following output:

Value Std. Error z p

(Intercept) 9.275 0.128 72.21 0.00e+000

cutsize1 -0.552 0.139 -3.97 7.06e-005

cutsize2 -0.670 0.100 -6.67 2.48e-011

slide16

Regression Analysis yielded the following results:

A step-wiseregressionanalysis of the data on S-Plus where the exponential distribution was assumed produced the following output:

Initial variables:

Value Std. Error z p

(Intercept) 11.0113 0.8091 13.6092 3.53e-042

cutsize1 -0.0615 0.1796 -0.3425 7.32e-001

cutsize2 -0.3278 0.1618 -2.0256 4.28e-002

lymph -0.7694 0.4661 -1.6508 9.88e-002

depth -0.0703 0.0146 -4.7977 1.61e-006

grad -0.5229 0.2063 -2.5349 1.12e-002

age 0.0142 0.0145 0.9758 3.29e-001

rad 0.0245 0.2966 0.0827 9.34e-001

Final variables:

Value Std. Error z p

(Intercept) 11.5989 0.5526 20.99 8.03e-098

cutsize1 -0.0660 0.1786 -0.37 7.12e-001

cutsize2 -0.3292 0.1609 -2.05 4.08e-002

lymph -0.7735 0.3973 -1.95 5.16e-002

depth -0.0666 0.0141 -4.71 2.46e-006

grad -0.5378 0.2063 -2.61 9.15e-003

slide17

Initial analysis showed that possible prognostic factors were Size, Lymph Nodes, Tumor Depth and Cell Grade

  • Cox’s Proportional Hazard reaffirmed that Size, Depth and Cell Grade were important diagnostic factors, but Lymph Nodes are only significant at the 10% level