Predictors of Clinical Outcomes: Fantasy and Facts. Lawrence B. Marks, M.D. Radiation Oncology Duke University Medical Center Durham, North Carolina

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1 Predictors of Clinical Outcomes: Fantasy and Facts Lawrence B. Marks, M.D. Radiation Oncology Duke University Medical Center Durham, North Carolina

2 Dose/volume Parameters Tumor outcome Normal tissue outcome Patient factors Tumor factors (grade, location) (pre-rt function, inherent sensitivity) Duke University

3 Pulmonary Toxicity: RT for Lung Cancer N Grade = 2 (%) Severe (%) Sunyach Monson Robnett Martel Segawa Armstrong Graham Oetzel Kwa Hernando Abratt 42 5

4 Cumulative DVH Points vs. Percent Volume at =D X V V30 30 whole curve MLD, NTCP Dose

5 Dosimetric Predictors of RT-Induced Martel Pulmonary Toxicity Normal Tissue Complication Probability V 25 (NTCP) (% > 25 Gy) Mean Lung Dose (MLD) Armstrong Oetzel Graham Kwa Hernando Duke University

6 Fan, JCO 19(2):543, 2001, Duke Univ.

7 50 Rate Pulmonary Toxicity(%) Mean Lung Dose (Gy) Oetzel (66) Kwa (400) Graham (99) Hernando (201)

8 Graham et al., Washington University Tox{ Yes No Sensitivity Specificity Pos. Pred.. Val. 18 Neg. Pred.. Val. 100 Graham IJROBP 45:323; 1999 V20 < >

9 Selection of cut-points is problematic Positive and negative predictive values depend on incidence Receiver Operating Characteristic (ROC) Curves Assess utility of predictor throughout a continuum of cut-points Duke University

10 Sensitivity ROC Curve B A chance Specificity

11 Area Under ROC Curve Pre-RT All Pts. DLCO Single DVH-Based Parameters > 40% V MLD Single SPECT-Based Parameters MPLD MLD Ratio (MPLD/MLD) ORP (DRC DFH) Multi-parameter parameter-based Models MLD & DLCO MPLD & DLCO OPR & DLCO DLCO & MLD Ratio (or MLD diff)

12 Role of TGFb Favorable TGFb and V30 < % Unfavorable TGFb or V30 = 30 18% Unfavorable TGFb and V30 = 30 41% Fu et al. IJROBP Duke University

13 Lung Injury: Endpoints Regional Global Symptomatic Asymptomatic Radiologic (chest x-ray, x CT perfusion scans) Shortness of Breath, cough Pulmonary Function Tests, 6 minute walk Duke University

14 Local dose fi local perfusion loss SPECT Local effects fi global functional changes pulmonary function tests, symptoms 6 minute walk Duke University

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18 % Reduction Regional Perfusion Regional Dose (Gy)

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20 MONTHS 9 MONTHS PERCENT REDUCTION IN PERFUSION 3 MONTHS 75 6 MONTHS DOSE (cgy) 12 MONTHS

21 1.5 Slope of DRC (% Reduction per Gy) From Woel et al, Duke Univ Months Post-RT

22 Percent (Perfused) Lung DVH (DFH) Vd Percent Reduction Regional Perfusion Rd d Dose d Dose Change in PFT = S(V d R d ) DLCO Duke University

23 Overall Group 60 y = x Actual Reduction DLCO (%) R = 0.30, p = Predicted Reduction in PFTs (%) Duke University

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26 Predicted vs.. Measured Decline in DLCO (R) # FU PFT s All Patients No Central Tumor With Adjacent Hypoperfusion = (59) 0.40 (28) = (43) 0.56 (17) = (22) 0.91 (8) Duke University

27 Central Lung Cancers Adjacent Hypoperfusion DLCO Improved No 1/20 Yes 8/20 P = 0.09 Marks, Cancer 1999 Duke University

28 Decline As Predicted Decline Less Than Predicted Increase or No Change Choi V/Q shift (22) 20% 20% 60% No shift (80) ~ 60% ~ 40% 0 Curran RT alone (43) 2% 20% ~ 70% Post-op op (19) 16% 37% 37% Lung Cancer 10 Suppl.. S219; 1994 IJROBP 24:31; 1992

30 Predictors of Lung Injury Not ideal May work better in subgroups Pre-RT function Tumor interactions Biologic factors Duke University

31 Clinical Realities High Risk Plan No reasonable alternative Local failure fi death Shortness of breath death \,, we treat anyway. Duke University

32 Local dose Local effect DVH D PFT DF(function)H Symptoms Patient-specific factors Duke University

33 Current Predictors Based on conventional techniques Probably NOT applicable with new treatment techniques Tracheal, bronchial injuries Esophageal > lung Duke University

34 Incidence of = Grade 3 Toxicities: Carolina Consortium (UNC, DUMC, Wake) Dose Carbo/Taxol Carbo/ Navelbine 73.6 Gy 0/7 1/8 Gr 3 Esoph 80.0 Gy 1/7 Gr 3 Esoph 1/7 Gr 3 Esoph 86.4 Gy 2/7 Gr 4 Lung 0/5 Gr 4 Esoph Exceeds MTD

35 Author Lingos Johansson Cossett Jensen Bentzen Mah Theuws Endpoint Symptoms CXR Symptoms CXR fl PFT fl PFT CXR CT SPECT Radiation Effect Endpoint fl Chemo Chemo Chemo Tobacco TAM Chemo Chemo Tobacco Tobacco Duke University

36 Predicting Lung Injury Patient-specific hetero large Compensation tumor tumor shrinkage Difficult parallel organ (liver, kidney, parotid easier?) Duke University

38 Specific Questions Are predictors reliable? Not yet. How should they be used? Carefully. Not to withhold treatment! Accuracy level needed? Depends on severity of outcome How to improve? Physiologic based studies Local vs.. global Organ structure/function Multifunction organs Duke University

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43 Acknowledgements M Fan, D Hollis, P Lind,, S Zhou, T Shafman,, R Jaszczak,, ER Coleman, M Munley,, P Hardenbergh Grant CA awarded by the NIH University of North Carolina for PLUNC treatment planning software Duke University

44 Radiation Oncology: Lawrence Marks, M.D. Ming Fan, M.D. Maria Hernando,, M.D. Mitchell Anscher, M.D. Tim Shafman,, M.D. Jean Poulson,, D.V.M., Ph.D. Pehr Lind,, M.D., Ph.D. Zeljko Vujaskovic, Ph.D. Data/Statistics: Robert Clough Donna Hollis, M.S. Andrea Tisch,, R.T.T. UNC: Julian Rosenman Radiation Physics: Su-Min Zhou, Ph.D. Kim Light, R.T.T., C.M.D. Gunilla Bentel, R.N., R.T.T. Michael Munley, Ph.D. Phil Antoine Jane Hoppenworth Nuclear Medicine: Terry Wong, M.D. Ronald Jaszczak, Ph.D. R.E. Coleman, M.D. NIH grants CA and R01-CA33541, and DOE grant DE-FG05 FG05-89ER60894 Duke University