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How Will My Patient Do: Nomograms and Predictive Models in Oncology. Peter Scardino, M.D. Chairman, Department of Urology Head, Prostate Cancer Program Memorial Sloan-Kettering Cancer Center New York. What is a Nomogram?.

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how will my patient do nomograms and predictive models in oncology
How Will My Patient Do: Nomograms and Predictive Models in Oncology

Peter Scardino, M.D.

Chairman, Department of Urology Head, Prostate Cancer Program

Memorial Sloan-Kettering Cancer Center

New York

what is a nomogram
What is a Nomogram?
  • Statistical definition: scales which you connect with a line, like a slide rule.
  • Practical definition: A device or model which uses an algorithm or mathematical formula to predict the probability of an outcome, optimized for predictive accuracy.
established factors that characterize prostate cancer
Established Factors that Characterize Prostate Cancer

Clinical stage (TNM) ~ Extent

Gleason patterns (1-5) ~ Grade or biologic aggressiveness

Serum PSA level (ng/ml) ~ Volume

slide4

Clinical Prognostic Factors

Each of these clinical prognostic factors (T-stage, grade, PSA) independently predicts pathologic stage and prognosis after treatment.

When they are combined, the accuracy of prediction increases.

nomogram for predicting pathologic stage
NOMOGRAM FOR PREDICTING PATHOLOGIC STAGE

Johns Hopkins, Baylor, U. Michigan SPOREs

PSA 4.1-10 PSA 10.1-20

Gleason Sum Clinical Stage Clinical Stage

T1c T2b T3a T1c T2b T3a

Organ-Confined

5 69 38 23 57 28 16

(63-74) (32-45) (13-38) (50-64) (22-34) (8-28)

7 48 21 11 36 14 7.2

(42-53) (17-25) (5.8-20) (30-42) (11-18) (4-14)

Modified rom Partin AW, Kattan MW, Subong ENP, Walsh PC, Wojno KJ, Oesterling JE, Scardino PT, Pearson JD. JAMA 1997; 277:1445.

nomogram for predicting pathologic stage1
NOMOGRAM FOR PREDICTING PATHOLOGIC STAGE

Johns Hopkins, Baylor, U. Michigan SPOREs

PSA 4.1-10 PSA 10.1-20

Gleason Sum Clinical Stage Clinical Stage

T1c T2b T3a T1c T2b T3a

Organ-Confined

5 69 38 23 57 28 16

(63-74) (32-45) (13-38) (50-64) (22-34) (8-28)

7 48 21 11 36 14 7.2

(42-53) (17-25) (5.8-20) (30-42) (11-18) (4-14)

Modified rom Partin AW, Kattan MW, Subong ENP, Walsh PC, Wojno KJ, Oesterling JE, Scardino PT, Pearson JD. JAMA 1997; 277:1445.

slide7

PSA Progression-free Probability after RP for cT1-3a Prostate Cancer

by Pathological Stage

Confined

ECE

SVI

LN+

slide8

0

10

20

30

40

50

60

70

80

90

100

Preoperative Nomogram for Prostate Cancer Recurrence

Points

(31)

(47)

(57)

= 135 pts

PSA

4

20

0.1

1

2

3

6

7

8

9

10

12

16

30

45

70

110

T2a

T2c

T3a

ClinicalStage

T1c

T1ab

T2b

Organ confined = 21%

 2+3

 4+

3+  2

Biopsy Gleason Grade

 2+  2

3+3

 3+ 4

135 pts

Total Points

0

20

40

60

80

100

120

140

160

180

200

47%

60MonthRec. Free Prob.

.96

.93

.9

.85

.8

.7

.6

.5

.4

.3

.2

.1

.05

Instructions for Physician: Locate the patient’s PSA on the PSA axis. Draw a line straight upwards to the Points axis to determine how many points towards recurrence the patient receives for his PSA. Repeat this process for the Clinical Stage and Biopsy Gleason Sum axes, each time drawing straight upward to the Points axis. Sum the points achieved for each predictor and locate this sum on the Total Points axis. Draw a line straight down to find the patient’s probability of remaining recurrence free for 60 months assuming he does not die of another cause first.

Note: This nomogram is not applicable to a man who is not otherwise a candidate for radical prostatectomy. You can use this only on a man who has already selected radical prostatectomy as treatment for his prostate cancer.

Instruction to Patient: “Mr. X, if we had 100 men exactly like you, we would expect between <predicted percentage from nomogram - 10%> and <predicted percentage + 10%> to remain free of their disease at 5 years following radical prostatectomy, and recurrence after 5 years is very rare.”

  • 1997 Michael W. Kattan and Peter T. Scardino

Kattan MW et al: JNCI 1998; 90:766-771.

patient population validation of preoperative recurrence nomogram
Patient population: validation of preoperative recurrence nomogram

USA Cleveland Clinic n= 1168 pts.

LSU n= 583 pts.

UCLA n= 617 pts.

USC n= 1501 pts.

Europe Hamburg n= 1134 pts.

Rotterdam n= 475 pts.

Australia Sydney n= 754 pts.

Total n= 6232 pts.

Concordance index 0.751

urologists vs preoperative nomogram
Urologists vs. Preoperative Nomogram
  • 10 case descriptions from 1994 MSKCC patients presented to 17 urologists
    • In addition to PSA, biopsy Gleason grades, and clinical stage, urologists were provided with patient age, systematic biopsy details, previous biopsy results, and PSA history.
  • Preoperative nomogram was provided.
  • Urologists were asked to make their own predictions of 5 year progression-free probabilities with or without use of the preoperative nomogram.
  • Concordance indices:
    • Nomogram = 0.67
    • Urologists = 0.55, p<0.05
slide13

Progression-free probability by risk group

Intermediate risk

Low risk

T2b or Gl 7 or PSA 10-20

*

T1c/T2a, Gl 2-6, PSA <10

High risk

T2c or Gl 8-10 or PSA >20

*

*

* p < 0.05

Mod. From D’Amico et al JAMA 280:969-74, 1998

palm pilot nomogram software program algorithm for prognosis and pathologic stage
Palm Pilot nomogram software program: algorithm for prognosis and pathologic stage
  • Includes pretreatment and postoperative predictions.
  • Uses published nomograms in prostate cancer.

Nomogram

Available at http://www.mskcc.org/prostate/nomograms

advantages of nomograms interpreting discordant results
Advantages of nomograms: interpreting discordant results
  • A 59 y.o. man has a poorly differentiated (Gleason grade 4 + 5 = 9) cancer in 1 biopsy core taken from an impalpable (cT1c) prostate because of a PSA of 6. How likely would surgery control this cancer? 83% 63% 43% 23% 3%
  • Answer: 83% (37% confined, 40% ECE, 15% SVI, 8% LN) Nomogram
  • A 53 y.o. man had a PSA 47 when first examined. There was a firm palpable nodule in the prostate (cT2a). Needle biopsy showed Gleason grade 3+3=6 cancer in 3 of 6 cores. Is this a “curable” lesion? What is the 5 yr. freedom from recurrence?88% 73% 58% 43% 28%
  • Answer: 58% (22% confined, 60% ECE, 10% SVI, 8% LN)
nomograms in oncology
Nomograms in Oncology
  • Prostate cancer
  • Kidney cancer
  • Sarcoma
  • Gastric cancer
  • Breast cancer
  • Melanoma
  • Colorectal carcinoma
  • Pancreatic cancer
  • Lung cancer
renal cancer prognosis postoperative nomogram

Renal Cancer Prognosis: Postoperative Nomogram_________________________________________________________________

Kattan M., Motzer R., Reuter V., and Russo P.

Department of Urology

Memorial Sloan-Kettering Cancer Center

New York, NY

J. Urol. 2001

postoperative prognostic nomogram for rcc
Postoperative Prognostic Nomogram for RCC

Instructions for Physician: Locate the patient’s symptoms (I=incidental, L=local, S=systemic) on the Symptoms axis. Draw a line straight upwards to the Points axis to determine how many points towards recurrence the patient receives for his symptoms. Repeat this process for the otheraxes, each time drawing straight upward to the Points axis. Sum the points achieved for each predictor and locate this sum on the TotalPoints axis. Draw a line straight down to find the patient’s probability of remaining recurrence free for 5 years assuming he or she does not die of another cause first.

Instruction to Patient: “Mr. X, if we had 100 men or women exactly like you, we would expect between <predicted percentage from nomogram – 10%> and <predicted percentage + 10%> to remain free of their disease at 5 years following surgery, though recurrence after 5 years is still possible.”

Kattan et al, J. Urol, 2001

slide21

Case History #2: 68 yo female presents with tumor found incidentally during ultrasound for gallbladder pain. Undergoes partial nephrectomy for 4cm chromophobe RCC.

slide22

Case History #3: 62 yo male presents with painless gross hematuria and undergoes resection of 10cm conventional clear cell carcinoma invading IVC.

predictive nomogram benefits
Predictive Nomogram: Benefits __________________________________________________
  • Patient counseling.
  • Equal risk stratification in clinical trials.
  • Entry of patients with poor prognosis into adjuvant clinical trials.
prostate cancer disease states nomograms predict transition rates between disease states
Prostate Cancer Disease States:Nomograms Predict Transition Rates Between Disease States

Cancer suspected (PSA, DRE)

Localized cancer

Rising PSA

Metastases

Post-castrate mets

Death, other Death, cancer

Salvage Rx

Modified from Scher et al Urology 2000

predictive models for prostate cancer
PREDICTIVE MODELS FOR PROSTATE CANCER
  • Patient counseling
  • Follow-up surveillance scheduling
  • Rational application of adjuvant therapy
  • Risk stratification for clinical trials
prostate cancer disease states
Prostate Cancer Disease States
  • Biopsy negative.
  • Need repeat biopsy?
  • Repeat biopsy nomogram

Cancer suspected (PSA, DRE)

Localized cancer

Rising PSA

Metastases

Post-castrate mets

Death, other Death, cancer

Salvage Rx

Modified from Scher et al Urology 2000

repeat biopsy multivariable analysis
Repeat biopsy: multivariable analysis

Lopez-Corona et al., In Press, J. Urol

repeat biopsy nomogram
Repeat biopsy nomogram

≤ 1/2 lobe

N

>1/2 lobe

Y

N

Y

N

PSA Slope

Y

N

Prob. +(Bx) 12 Mo. from first neg Bx

Prob. +(Bx) 24 Mo. from first neg Bx

Prob. +(Bx) 36 Mo. from first neg Bx

prostate cancer disease states1
Prostate Cancer Disease States

Cancer suspected (PSA, DRE)

Localized cancer

Rising PSA

Metastases

Post-castrate mets

Death, other Death, cancer

  • Needs aggressive treatment?
  • Indolent cancer nomogram

Salvage Rx

Modified from Scher et al Urology 2000

indolent prostate cancer
Indolent prostate cancer
  • total tumor volume <0.5cc
  • confined to the prostate (no focal or established extracapsular extension)
  • no Gleason pattern 4 or 5 in RP specimen
indolent prostate cancer dataset
Indolent prostate cancer dataset
  • RRP between August 1, 1986 and March 1, 2000
    • Baylor College of Medicine (n=572)
    • University Hospital Hamburg-Eppendorf (n=450)
    • All men had to have systematic needle biopsy (> 6 cores)
  • Exclusions:
    • pretreatment PSA > 20
    • primary or secondary Gleason grade 4 or 5 cancer in biopsy
    • positive cores > 50%
    • total cancer in biopsy cores > 20mm
    • benign tissue in all cores < 40mm
  • Left 409 men for analysis (indolent N=80, 20%)
base indolent nomogram
Base indolent nomogram

Pre.Tx.PSA

Pri.Bx.Gl

Sec.Bx.Gl

Prob. Indolent Ca.

full indolent nomogram
Full indolent nomogram

Pre.Tx.PSA

Clin. Stage

Pri.Bx.Gl

Sec.Bx.Gl

U/S Vol

mm Cancer

mm nonCa

Prob. Indolent Ca.

prostate cancer disease states2
Prostate Cancer Disease States

Cancer suspected (PSA, DRE)

Localized cancer

Rising PSA

Metastases

Post-castrate mets

Death, other Death, cancer

  • What are the pathologic features of the cancer?

Salvage Rx

Modified from Scher et al Urology 2000

predicting pathologic stage
Predicting Pathologic Stage
  • Organ confined – DRE, PSA, biopsy Gleason grade, %cores +, mm cancer, mm non-cancer
  • Side of extracapsular extension – side-specific DRE and biopsy results, PSA
  • Seminal vesicle invasion – DRE, PSA, biopsy Gleason grade, % cancer in cores at the base
  • Lymph node metastases – DRE, PSA, biopsy Gleason grade, your % LN+.
prostate cancer disease states3
Prostate Cancer Disease States

Cancer suspected (PSA, DRE)

Localized cancer

Rising PSA

Metastases

Post-castrate mets

Death, other Death, cancer

  • How well will each treatment work?

Salvage Rx

Modified from Scher et al Urology 2000

slide41

Preoperative Nomogram for Prostate Cancer Recurrence

0

10

20

30

40

50

60

70

80

90

100

Points

PSA

4

20

0.1

1

2

3

6

7

8

9

10

12

16

30

45

70

110

T2a

T2c

T3a

ClinicalStage

T1c

T1ab

T2b

 2+3

 4+

3+  2

Biopsy Gleason Grade

 2+  2

3+3

 3+ 4

Total Points

0

20

40

60

80

100

120

140

160

180

200

60MonthRec. Free Prob.

.96

.93

.9

.85

.8

.7

.6

.5

.4

.3

.2

.1

.05

Instructions for Physician: Locate the patient’s PSA on the PSA axis. Draw a line straight upwards to the Points axis to determine how many points towards recurrence the patient receives for his PSA. Repeat this process for the Clinical Stage and Biopsy Gleason Sum axes, each time drawing straight upward to the Points axis. Sum the points achieved for each predictor and locate this sum on the Total Points axis. Draw a line straight down to find the patient’s probability of remaining recurrence free for 60 months assuming he does not die of another cause first.

Note: This nomogram is not applicable to a man who is not otherwise a candidate for radical prostatectomy. You can use this only on a man who has already selected radical prostatectomy as treatment for his prostate cancer.

Instruction to Patient: “Mr. X, if we had 100 men exactly like you, we would expect between <predicted percentage from nomogram - 10%> and <predicted percentage + 10%> to remain free of their disease at 5 years following radical prostatectomy, and recurrence after 5 years is very rare.”

Nomogram

  • 1997 Michael W. Kattan and Peter T. Scardino

Kattan MW et al: JNCI 1998; 90:766-771.

existing nomograms for prostate cancer
Existing Nomograms for Prostate Cancer
  • Pathologic stage
  • Radical prostatectomy: preoperative (5 year)
  • 3D conformal external beam radiation therapy
    • Biochemical progression (5 year)
    • Metastases (7 year)
  • Brachytherapy (5 year)
  • Radical prostatectomy: postoperative (7 year)
prostate cancer disease states4
Prostate Cancer Disease States

Cancer suspected (PSA, DRE)

Localized cancer

Rising PSA

Metastases

Post-castrate mets

Death, other Death, cancer

  • Improved predictions

Salvage Rx

Modified from Scher et al Urology 2000

postoperative nomogram for psa progression after radical prostatectomy
Postoperative Nomogram for PSA Progression after Radical Prostatectomy

C-Index: 0.80

From Kattan MW, Scardino PT et al. J Clin Oncol 1999

why a new postoperative nomogram
WHY A NEW POSTOPERATIVE NOMOGRAM?
  • Improved prognosis of prostate cancer in the recent era independent of stage, grade, PSA
    • Cagiannos et al. J Urol 2004
  • Patients receiving adjuvant radiation therapy were considered treatment failures in the original nomogram
  • Nomogram predicts the 7-year PFP  many patients remain at risk after 7 years
    • 10-year PFP is optimal endpoint for biochemical progression as the risk of progression after 10 years is 3% (95% CI, 0-7%)
  • Changing prognosis based on disease-free interval status
    • A nomogram that recalculates patient’s prognosis for a disease-free interval that he has achieved would be useful for patient counseling and follow-up scheduling
changing prognosis based on disease free interval maintained
CHANGING PROGNOSIS BASED ON DISEASE-FREE INTERVAL MAINTAINED

* As defined by PSA < 0.2 ng/mL within preceding 12 months

patients and methods
PATIENTS AND METHODS
  • Cox proportional hazards regression analysis  model the pre- and postoperative clinical data of 2055 pts with clinically localized prostate cancer who underwent radical prostatectomy by 1 of 2 surgeons between 1983 and 2003 without prior therapy
  • Variables included in nomogram:
  • Patients with null values excluded  1881 eligible patients

* Treated as time-dependent covariate

endpoint
ENDPOINT
  • Disease progression:
    • PSA 0.4 or greater and a confirmatory rise (time of failure is date of 2nd PSA rise)
    • Initiation of androgen-deprivation therapy after RP
    • Initiation of external-beam radiation therapy > 1 year after RP
    • Clinical disease recurrence
    • Death from prostate cancer
  • Patients censored if lost to follow-up or death from causes other than prostate cancer
nomogram validation
NOMOGRAM VALIDATION
  • Nomogram applied to independent cohort
  • 2103 patients who underwent radical prostatectomy at MSKCC between 1985-2003 who were not included in modeling cohort
  • No patient received prior therapy before RP
  • Patients censored at the time of adjuvant radiation therapy
disease progression after radical prostatectomy
DISEASE PROGRESSION AFTER RADICAL PROSTATECTOMY

Modeling set

Validation set

P = .06

At Risk 1881 971 746 431 236 130 43 11

1782 927 692 347 166 25 0 0

slide54

UPDATED AND ENHANCED POSTOPERATIVE NOMOGRAM PREDICTING

10-YEAR PFP AFTER RADICAL PROSTATECTOMY ALONE

Months from Surgery

C-Index 0.81

nomogram calibration bootstrap corrected predictions based on modeling set
NOMOGRAM CALIBRATION: Bootstrap-Corrected Predictions Based on Modeling Set

Actual Proportion Free from Recurrence at 10 yrs

Nomogram Predicted 10-Year Probability

C-index: 0.86

nomogram calibration validation set
NOMOGRAM CALIBRATION: Validation Set

Actual Fraction Free of Recurrence

Nomogram Predicted Probability of Freedom from Recurrence

hypothetical patient
HYPOTHETICAL PATIENT
  • Preoperative PSA 8.2
  • Prostatectomy Gleason sum 3 + 4
  • Extacapsular extension
  • Positive surgical margins
  • No lymph node involvement
  • Radical prostatectomy in 2004
  • No adjuvant radiation therapy
slide58

HYPOTHETICAL PATIENT

Months from Surgery

Total points: 134

Immediately postop.

10-year PFP: 80%

134 pts

slide59

HYPOTHETICAL PATIENT

Months from Surgery

Same patient.

Same points (134).

Now 2 years without evidence of disease*.

Revised 10-year PFP from the time of RP: 85%

134 pts

* PSA < 0.2 ng/mL within the preceding 12 months

slide60

HYPOTHETICAL PATIENT

Months from Surgery

Same patient.

Same points (134).

Now 5 years without evidence of disease.

Revised 10-year PFP from the time of RP: 91%

134 pts

* PSA < 0.2 ng/mL within the preceding 12 months

slide61

Molecular and Genomic Prognostic Factors

Question: How can we improve our ability to predict the threat posed by a prostate cancer using modern molecular, genetic, and proteomic analyses?

slide63

Levels of discrimination for current prostate cancer nomograms

Zero ability to predict

Predict Perfectly

Need to move this way

0.5

0.6

0.7

0.8

0 .9

1.0

OC

Gail

Breast Ca

Preop with IL-6 & TGFβ1

LN+

Survival with progressive metastatic disease

Indolent Ca

Postoperative

Sarcoma

Positive subsequent biopsy

Gastric

Radiotherapy

Renal Cell

Pancreatic

Preoperative

Brachytherapy

microarrays and prostate cancer
Microarrays and Prostate Cancer
  • Single marker insufficient to explain the biological behavior of prostate cancer
  • Expression of several genes more informative
  • High-throughput oligonucleotide microarrays:
    • Analyze expression of ~20,000 genes (mRNA) simultaneously
    • Potential to identify prognostic genes in unbiased manner
genes associated with recurrent cancer
Genes Associated with Recurrent Cancer
  • Highest ranked genes:
    • EI24 – Etoposide induced 2.4 mRNA (PIG8)
    • EPB49 – Erythrocyte membrane protein band 4.9
    • MAP4K4 – Mitogen-activated protein kinase 4 kinase
  • Most genes have not been implicated in CaP
  • Several genes known to play role in CaP:
    • EPB49
    • GST-Pi*
    • GST-M1
    • ACPP – prostatic acid phosphatase
    • FAT tumor suppressor homolog 1
    • TGF beta-3
  • 5 genes in 17-gene metastasis signature:
    • MYH11, MYLK, CNN1, ACTG2, HNRPC
slide67

Gene Expression Model for Recurrence

  • 6-gene recurrent prostate cancer signature was most common
  • Classification accuracy: 75%
    • 70% recurrent samples
    • 79% non-recurrent samples
  • EI24, EPB49 and MAP4K4 selected as the top 3 genes in 78 or 79 models
    • 46 genes selected overall
  • C-index: 0.75

P< 0.001

slide68

Combined Clinical and Molecular Nomogram

  • Nomogram prediction was always the 1st variable in all the models
  • A 4-gene recurrent cancer molecular signature was added to the nomogram prediction
  • Classification accuracy: 89%
    • 32/37 recurrent samples (86%)
    • 38/42 non-recurrent samples (90%)
  • EPB49, APP, SSR1, ACPP accounted for 75% of all genes selected (24 overall)
  • EI24 was not chosen in any model
  • C-index: 0.89

P< 0.001

molecular profiling and predictive models for prostate cancer
Molecular Profiling and Predictive Models for Prostate Cancer
  • Integration of gene expression signatures and standard clinical variables produces a predictive model for prostate cancer recurrence that performs significantly better than those based on either information alone
  • The improvement in predictive accuracy with the combined model was mainly seen for patients with nomogram predictions in the middle range
  • Gene expression differences alone do not predict outcome as accurately as the models based on standard clinical variables
future nomograms for prostate cancer
Future Nomograms for Prostate Cancer
  • Radical prostatectomy – 12 year risk of metastases and cancer-specific mortality
  • Radiation therapy for rising PSA after RP
  • Rising PSA after RP
    • Probability of + bone scan
    • Metastases at 8 years
    • Response to hormonal therapy
when the patient wants a prediction what options does the clinician have
When The Patient Wants A Prediction, What Options Does The Clinician Have?
  • Quote an overall average to all patients
  • Deny ability to predict at the individual patient level
  • Assign the patient to a risk group, i.e. high, intermediate, or low
  • Predict based on knowledge and experience
  • Apply a nomogram