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1 Supplementary Online Content Lakdawalla DN, Chou JW, Linthicum MT, MacEwan JP, Zhang J, Goldman DP. Evaluating expected costs and benefits of granting access to new treatments on the basis of progression-free survival in non small-cell lung cancer. JAMA Oncol. Published online March 19, doi: /jamaoncol eappendix. Supplementary Materials Data, Parameters, and Calculations etable 1. Net PFS and OS Means by Trial etable 2. Expected Values by PFS Net Benefit Threshold etable 3. Incremental Treatment Costs etable 4. Incremental Social Value by PFS Net Benefit Threshold etable 5. Indifference Points for Payers When Choosing Between OS and PFS Policies etable 6. Expected Net Benefit for Median PFS and OS etable 7. Expected and Incremental Social Value for Median PFS and OS Analysis etable 8. Indifference Points for Median PFS and OS Analysis etable 9. Incremental Social Value by PFS Benefit Threshold and Value of a Statistical Life Year etable 10. Incremental Social Value by PFS Benefit Threshold and Incremental Lifetime Treatment Cost etable 11. NSCLC Trials With Separate PFS and OS Publications, etable 12. Incremental Social Value by PFS Benefit Threshold and Publication Delay etable 13. Parameter Values Used for Sensitivity Analyses

2 etable 14. Sensitivity Analysis Scenarios Results etable 15. Net PFS Benefits for Clinical Uncertainty Sensitivity Analysis etable 16. Clinical Uncertainty and Publication Bias Sensitivity Analysis Results ereferences This supplementary material has been provided by the authors to give readers additional information about their work.

3 eappendix. Supplementary Materials Data, Parameters, and Calculations Framework for estimating value of alternative policies We first develop a framework for calculating the expected social value (or cost) of policies that grant early access to drugs on the basis of PFS data alone, compared to policies that wait for OS data before granting access. We build this framework by considering the range of possible decisions and outcomes. First, consider the case where access is granted based on PFS data before data on OS outcomes are available. In this case, access would not be granted for drugs with PFS benefit below some chosen threshold of months (e.g., zero months of PFS benefit, 1 month of PFS benefit, and so on). The social value of early access based on PFS data (NB PFS ) depends on: the probability of success; the complementary probability of error; the benefits of success, which we define below; the cost of failure, also defined below; the months of delay in waiting for data on OS outcomes (t OS t PFS ); the number of patients that would be treated each month ; the lifespan of the drug (T); the lifetime incremental cost of treatment (c), and the value of a statistical life month (v). When the payer chooses to grant access based on PFS, there are four true states of the world underlying her decision: 1. Positive PFS outcomes and positive OS outcomes; 2. Positive PFS outcomes and negative OS outcomes; 3. Negative PFS outcomes and positive OS outcomes; and 4. Negative PFS outcomes and negative OS outcomes. In the first two cases, payers could grant access based on the PFS data and patients would have access for T months, but in the second scenario they would revoke access after the OS data became available, and the drug would only be available for the period of time between the PFS and OS outcomes being revealed (t OS t PFS ). In the third case, payers would only approve after the OS data became available, and patients would have access for (T t OS ) months. In the last scenario,

4 payers would never grant access. Thus, the expected net benefit of proceeding with PFS data equals the expected benefit from proceeding when PFS exceeds the critical threshold and OS benefit is positive less the expected cost of proceeding with PFS when PFS exceeds and OS has negative outcomes: EB Pr 0, E B B 0,B c Pr 0, E B B 0,B c. (1.1) Similarly, the expected benefit of waiting for OS data equals: EB Pr 0 E B B 0,B c. (1.2) The expected net benefit of granting access based on the PFS data rather than waiting for the OS data is the difference between (1.1) and (1.2), which simplifies to: ENB (1.3) Pr 0 E B B 0,B c Pr 0 E B B 0,B c Note that this term scales proportionally with the number of patients newly treated per month,. Thus, in order to avoid having to make assumptions about the size of the patient population that will be treated, we divide this term by, and recover the expected net benefit per new patient treated every month. We call this

5 the incremental social value of early access for an additional patient per month, or incremental social value for short. Mathematically, incremental social value is: ISV (1.4) Pr 0 E B B 0,B c Pr 0 E B B 0,B c We estimate the incremental social value of granting access to novel therapies for NSCLC by parameterizing equation 1.4 for alternative values of. The first term represents the number of additional months patients have to wait for access when OS requirements delay access to drugs. The second term in curly brackets represents the net change in survival per patient that results from delay. Both of these are multiplied by the value of survival gains. If expected net benefit is greater than zero, this means that the expected benefits of early access outweigh its expected costs, and vice versa. A complete derivation of this value framework is also described in Stevens et al (2014). 1 Data Collection The discussion above suggests that the following pieces of information are needed in order to quantify incremental social value: 1. The lifespan of an average cancer drug 2. The delay due to use of OS, instead of PFS; 3. The correlation between PFS and OS within a disease area; this correlation is sufficient to produce all the probability estimates and conditional expectations of interest (Pr 0 ; 0, ; Pr 0 ; E B B 0,B. 4. The value of a statistical life month, ; 5. The incremental lifetime cost of treatment,.

6 Below, we describe how each of these is estimated. Drug lifespan A systematic review of cancer drug utilization relative to years from FDA approval/drug launch indicates that peak utilization tends to occur around year 7 or 8 and begins to decline by year 9. 2 As such, we estimated the drug lifespan in our model to be 108 months. Data on delay, OS, and PFS Data on overall survival (OS), progression free survival (PFS), and delay between availability of PFS and OS results were extracted from phase 3 clinical trials for non small cell lung cancer (NSCLC) published between 2009 and As described in the manuscript, the following three inclusion criteria were used: 1) inclusion of progression free survival (PFS) or overall survival (OS) outcomes; 2) comparison of two or more treatments; and 3) inclusion of Kaplan Meier tables for the number of patients at risk for each time interval (see Appendix Table 1). A secondary targeted search was conducted within the collected trials for instances of separate publications for PFS and OS results from the same trial. From the Kaplan Meier tables published in each article we extracted the probability that a trial participant on the intervention or comparator drug would have survived at each time interval after randomization. These probabilities were used to calculate the mean PFS and OS for each treatment arm in every trial; these calculations are discussed below. Expected OS benefit when PFS is above a given threshold is the product of two variables: the average OS benefit across trials with PFS benefits at or above the threshold, and the probability of a positive (or negative) OS benefit for trials with PFS above the threshold. These variables were calculated separately for cases where net OS effect is positive and negative. Average OS benefit given PFS benefit

7 The average OS benefit, conditional on a PFS threshold, is calculated simply as the average OS benefit across trials that meet or exceed the PFS threshold. As discussed in the manuscript, we used estimated mean survival data instead of median survival data and conducted a sensitivity analysis based on the reported median survival data. Clinical trials typically measure and report median survival because censoring and the skewed nature of survival data can make mean survival difficult to estimate, but patients may find the mean or expected survival time more meaningful. 3,4 Therefore, we estimated mean survival time based on data provided in published trial results. These calculations are described below. Using the Kaplan Meier tables reported in each clinical trial for the number of patients remaining or at risk at each time interval, we estimated the share of patients in each treatment arm still alive at each time interval. That is, the height of the survival curve or Pr, where n j denotes the number of patients in treatment arm k (intervention, I, or comparator, C) surviving until period j and N k represents the total number of patients in the treatment arm. We then calculated the mean survival time as Pr The mean survival time equals the area under the survival curve at time J. The net mean survival time, or used as an input in our patient benefit model (described below), equals

8 We estimate both the net mean PFS and OS times, and. Please see Appendix Table 1 below for the list of trials and their and values. Probability of positive (or negative) OS effect Next, we calculated the share of trials with both positive OS and PFS above the threshold, i.e., Pr 0,. This probability of success equals the share of trials with positive OS and PFS outcomes. We also calculated the share of trials where the positive PFS outcome incorrectly predicted the OS outcome, i.e., Pr 0,. This probability of error equals the share of trials with positive PFS outcomes that had negative OS outcomes.

9 etable 1. Net PFS and OS Means by Trial Paper Intervention Drug Comparator Drug BPFS BOS Wu (2013) 5 erlotinib+gemcitabine gemcitabine cisplatin/carboplatin cisplatin/carboplatin Zukin (2013) 6 carboplatin + pemetrexed pemetrexed Quoix (2011) 7 carboplatin + paclitaxel vinorelbine/gemcitabine Shaw (2013) 8 crizotinib pemetrexed/docetaxel Mitsudomi gefitinib cisplatin + docetaxel (2010) 9 Herbst erlotinib + erlotinib (2011) 10 bevacizumab Morabito cisplatin + gemcitabine gemcitabine (2013) 11 Paz Ares sorafenib + gemcitabine + cisplatin (2012) 12 gemcitabine + cisplatin Rodrigues pemetrexed + docetaxel + carboplatin Pereira (2011) 13 carboplatin Wu (2012) 14 gefitinib carboplatin + paclitaxel Mok (2009) 15 Gefitinib Carboplatin + paclitaxel Patel (2013) 16 pemetrexed + paclitaxel + carboplatin carboplatin + bevacizumab bevacizumab Herbst vandetanib + docetaxel docetaxel (2010) 17 Johnson bevacizumab + bevacizumab (2013) 18 erlotinib Ridolfo IL2 + cisplatin + cisplatin + gemcitabine (2011) 19 gemcitabine Shi (2013) 20 icotinib gefitinib

10 etable 1. Net PFS and OS Means by Trial, continued Kim (2008) 21 gefitinib docetaxel Reck (2014) 22 nintedanib docetaxel Kubota vinorelbine + carboplatin + paclitaxel (2008) 23 gemcitabine + docetaxel Lee (2010) 24 gefitinib docetaxel Scagliotti sunitib + erlotinib erlotinib (2012) 25 Okamoto S1 + carboplatin paclitaxel + carboplatin (2010) 26 Boni (2012) 27 ifosfamide + gemcitabine gemcitabine + vinorelbine/cisplatin cisplatin/vinorelbine Kim (2013) 28 cetuximab + pemetrexed pemetrexed Treat gemcitabine + paclitaxel + carboplatin (2010) 29 carboplatin Treat gemcitabine + paclitaxel + carboplatin (2010) 29 paclitaxel Bepler gemcitabine + gemcitabine + carboplatin (2013) 30 carboplatin, docetaxel + carboplatin, gemcitabine + docetaxel, docetaxel + vinorelbine Boni (2012) 27 vinorelbine + gemcitabine (ifosfamide) cisplatin + gemcitabine (ifosfamide)

11 Expected OS effect Last, we calculated the expected net benefit to each patient treated for successes and failures. The former value, 0,, equals the expected gain in OS to patients from using the intervention drug rather than the comparator when the PFS data correctly predicts a positive OS benefit, or the benefits of success. This expected change in survival represents the gain in survival from correctly predicting the positive OS benefit with the PFS data. The latter value, 0,, equals the expected change in OS patients get from using the intervention drug when the PFS data incorrectly predicts a positive OS benefit, or the cost of errors. This expected change in survival represents the cost of the error of granting access to a therapy based on positive PFS outcomes when the OS outcomes turn out to be negative. Please see Appendix Table 2 below with total overall expected values by PFS net benefit threshold. etable 2. Expected Values by PFS Net Benefit Threshold PFS net benefit threshold Overall E(OS PFS>x) Delay Between Availability of PFS and OS Results Exactly one publication pair was identified within our defined literature sample, with a delay of 22 months between publication of the PFS and OS outcomes data. 15,31 Using expanded literature search criteria that eliminate the restriction to Phase III trials and the restriction to studies with Kaplan Meier tables, we also

12 obtain four additional publication pairs, with delays ranging from 7 months to 46 months. We use 7 months as our low scenario for delay and 46 months as our high scenario. Value of a Statistical Life Year As described in the manuscript, we consider a range of values for life expectancy, from $40,000 to $400,000; for our medium patient benefit parameter estimate, we use the Consumer Price Index to inflate a mid range value of $150,000 in 1997 dollars to $217,717 in 2013 dollars. 32,33 For the purposes of the model, we round down the inflated 2013 dollar value to $200,000 for VSLY. Given that the mean change in survival for NSCLC patients in measured in months, we use a value of $16,667 per life month. We also consider low and high VSLY scenarios of $100,000 and $300,000, respectively, with corresponding per month values. Incremental Lifetime Cost of Treatment To calculate the incremental cost per patient for a novel treatment, we conducted a targeted literature review for cost effectiveness analyses that used US costs for NSCLC treatments. We found four published studies, with incremental treatment costs ranging from $2,000 62,000, depending on the drug and its comparator (see Appendix Table 3 below) We computed the medium scenario by using the mean incremental cost from these studies of approximately $22,000 per patient. The low and high scenario values are given by $2000 and $62,000, the minimum and maximum values. Incremental treatment cost is defined as the difference between the total lifetime cost of treatment for patients using the intervention drug and the total lifetime cost of treatment for patients using the comparator drug.

13 etable 3. Incremental Treatment Costs Paper Intervention Comparator Incremental Cost Dollar Year Incremental cost in 2013 dollars Klein pemetrexed (non best supportive care $31, $34,687 (2010) 36 squamous) Klein pemetrexed (non erlotinib $24, $26,575 (2010) 36 squamous) Klein pemetrexed (non bevacizumab $9, $9,976 (2010) 36 squamous) Klein pemetrexed (all) best supportive care $28, $30,679 (2010) 36 Klein pemetrexed (all) erlotinib $18, $19,700 (2010) 36 Carlson pemetrexed docetaxel $4, $5,230 (2008) 35 Carlson pemetrexed erlotinib $6, $7,620 (2008) 35 Carlson docetaxel erlotinib $2, $2,390 (2008) 35 Shah (2013) 37 pemetrexed + paclitaxel + $19, $20,780 platinum carboplatin Shah (2013) 37 paclitaxel + paclitaxel + $39, $42,439 carboplatin + bevacizumab carboplatin Shah (2013) 37 pemetrexed + paclitaxel + $20, $22,190 platinum (chemo only) carboplatin Shah (2013) 37 paclitaxel + paclitaxel + $37, $40,541 carboplatin + bevacizumab (chemo only) carboplatin Bajaj erlotinib bevacizumab + $20, $20,116 (2014) 34 paclitaxel + carboplatin Bajaj (2014) 34 erlotinib paclitaxel + carboplatin $62, $62,745

14 Bajaj (2014) 34 Bajaj (2014) 34 Bajaj (2014) 34 erlotinib pemetrexed + carboplatin erlotinib bevacizumab + pemetrexed + carboplatin bevacizumab + pemetrexed + pemetrexed + carboplatin carboplatin $31, $31,438 $20, $20,359 $11, $11,079

15 Estimates of incremental social value Please see Appendix Table 4, below, for the incremental social value calculations that result from parameterizing the quantitative framework with the data described above. The table reports values based on medium scenario parameters. etable 4. Incremental Social Value by PFS Net Benefit Threshold PFS net benefit threshold Incremental social value 0 $170, $143, $73, $175, $175, $560, $560, Indifference Curves Finally, we identify the values of incremental lifetime treatment cost and of statistical life years at which payers are indifferent between PFS and OS policies. Specifically, we calculate the pair of values for treatment cost and value of life years that generate a net benefit of exactly zero. This enabled us to produce curves at which payers should be indifferent between an OS or PFS access decision. Please see Appendix Table 5 below for the incremental lifetime treatment cost values that generate payer indifference, given a VSLY and PFS net benefit threshold.

16 etable 5. Indifference Points for Payers When Choosing Between OS and PFS Policies Incremental Lifetime Treatment Cost Value of a Life Year PFS threshold >0 PFS threshold 1 PFS threshold 2 PFS threshold 3 $40,000 $ 2,848 $ 5,070 $ 5,998 $ 9,497 $60,000 $ 4,272 $ 7,605 $ 8,997 $ 14,246 $80,000 $ 5,696 $ 10,141 $ 11,995 $ 18,995 $100,000 $ 7,120 $ 12,676 $ 14,994 $ 23,743 $120,000 $ 8,544 $ 15,211 $ 17,993 $ 28,492 $140,000 $ 9,968 $ 17,746 $ 20,992 $ 33,241 $160,000 $ 11,392 $ 20,281 $ 23,991 $ 37,989 $180,000 $ 12,815 $ 22,816 $ 26,990 $ 42,738 $200,000 $ 14,239 $ 25,351 $ 29,989 $ 47,487 $220,000 $ 15,663 $ 27,886 $ 32,987 $ 52,235 $240,000 $ 17,087 $ 30,422 $ 35,986 $ 56,984 $260,000 $ 18,511 $ 32,957 $ 38,985 $ 61,733 $280,000 $ 19,935 $ 35,492 $ 41,984 $ 66,481 $300,000 $ 21,359 $ 38,027 $ 44,983 $ 71,230 $320,000 $ 22,783 $ 40,562 $ 47,982 $ 75,979 $340,000 $ 24,207 $ 43,097 $ 50,981 $ 80,727 $360,000 $ 25,631 $ 45,632 $ 53,980 $ 85,476 $380,000 $ 27,055 $ 48,167 $ 56,978 $ 90,225 $400,000 $ 28,479 $ 50,703 $ 59,977 $ 94,973

17 Sensitivity Analyses Calculated means sensitivity As a sensitivity analysis, we re calculated the probabilities and values for our sample using the median PFS and OS instead of our calculated means. Appendix Table 6, below, displays the net benefits based on the median changes in PFS and OS. etable 6. Expected Net Benefit for Median PFS and OS Paper Intervention Drug Comparator Drug BPFS BOS Wu (2013) 5 erlotinib+gemcitabine + gemcitabine cisplatin/carboplatin cisplatin/carboplatin Zukin carboplatin + pemetrexed 3 4 (2013) 6 pemetrexed Quoix carboplatin + paclitaxel vinorelbine/gemcitabine (2011) 7 Shaw (2013) 8 crizotinib pemetrexed/docetaxel Herbst erlotinib + bevacizumab erlotinib (2011) 10 Morabito cisplatin + gemcitabine gemcitabine (2013) 11 Paz Ares sorafenib + gemcitabine gemcitabine + cisplatin (2012) 12 + cisplatin Rodrigues pemetrexed + docetaxel + carboplatin Pereira (2011) 13 carboplatin Wu (2012) 14 gefitinib carboplatin + paclitaxel Mok (2009) 15 Gefitinib Carboplatin + paclitaxel Patel pemetrexed + paclitaxel + carboplatin (2013) 16 carboplatin + bevacizumab bevacizumab Herbst vandetanib + docetaxel docetaxel (2010) 17 Johnson bevacizumab + erlotinib bevacizumab (2013) 18 Ridolfo IL2 + cisplatin + cisplatin + gemcitabine (2011) 19 gemcitabine Shi (2013) 20 icotinib gefitinib

18 Kim (2008) 21 gefitinib docetaxel Reck nintedanib docetaxel (2014) 22 Kubota vinorelbine + carboplatin + paclitaxel (2008) 23 gemcitabine + docetaxel Lee (2010) 24 gefitinib docetaxel Scagliotti sunitib + erlotinib erlotinib (2012) 25 Okamoto S1 + carboplatin paclitaxel + carboplatin (2010) 26 Boni (2012) 27 ifosfamide + gemcitabine gemcitabine vinorelbine/cisplatin cisplatin/vinorelbine Kim (2013) 28 cetuximab + pemetrexed pemetrexed Treat gemcitabine + paclitaxel + carboplatin (2010) 29 carboplatin Treat gemcitabine + paclitaxel paclitaxel + carboplatin (2010) 29 Bepler gemcitabine + gemcitabine + carboplatin (2013) 30 carboplatin, docetaxel + carboplatin, gemcitabine + docetaxel, docetaxel + vinorelbine Boni (2012) 27 vinorelbine + gemcitabine (ifosfamide) cisplatin + gemcitabine (ifosfamide)

19 Appendix Table 7, below, contains the results of the expected and incremental social value calculations for the sensitivity analysis using median PFS and OS. etable 7. Expected and Incremental Social Value for Median PFS and OS Analysis PFS net benefit threshold Overall E(OS PFS>x) Incremental social value 0 1 $117, $79, $163, $291, $518, $518, $286, Finally, we replicated the break even (indifference curve) analysis using the calculations from the median PFS and OS analysis. The lifetime incremental treatment cost values at which a decision maker would be indifferent to providing access at PFS data availability rather than waiting for OS data for each value of a statistical life year can be found in Appendix Table 8, below.

20 etable 8. Indifference Points for Median PFS and OS Analysis Incremental Lifetime Treatment Cost Value of a Life Year PFS threshold >0 PFS threshold 1 PFS threshold 2 PFS threshold 3 $40,000 $ 3,333 $ 5,889 $ 9,111 $ 7,000 $60,000 $ 5,000 $ 8,833 $ 13,667 $ 10,500 $80,000 $ 6,667 $ 11,778 $ 18,222 $ 14,000 $100,000 $ 8,333 $ 14,722 $ 22,778 $ 17,500 $120,000 $ 10,000 $ 17,667 $ 27,333 $ 21,000 $140,000 $ 11,667 $ 20,611 $ 31,889 $ 24,500 $160,000 $ 13,333 $ 23,556 $ 36,444 $ 28,000 $180,000 $ 15,000 $ 26,500 $ 41,000 $ 31,500 $200,000 $ 16,667 $ 29,444 $ 45,556 $ 35,000 $220,000 $ 18,333 $ 32,389 $ 50,111 $ 38,500 $240,000 $ 20,000 $ 35,333 $ 54,667 $ 42,000 $260,000 $ 21,667 $ 38,278 $ 59,222 $ 45,500 $280,000 $ 23,333 $ 41,222 $ 63,778 $ 49,000 $300,000 $ 25,000 $ 44,167 $ 68,333 $ 52,500 $320,000 $ 26,667 $ 47,111 $ 72,889 $ 56,000 $340,000 $ 28,333 $ 50,056 $ 77,444 $ 59,500 $360,000 $ 30,000 $ 53,000 $ 82,000 $ 63,000 $380,000 $ 31,667 $ 55,944 $ 86,556 $ 66,500 $400,000 $ 33,333 $ 58,889 $ 91,111 $ 70,000 In addition to testing the sensitivity of the model to the use of calculated means as compared to reported medians, we also simulated the effect of using the low and high values for the following model parameters: value of a statistical life year, treatment cost, and publication delay. Finally, to assess robustness to clinical uncertainty about the correlation between PFS and OS, we also simulated the effect of publication bias on our model, as described in the manuscript. Value of a Statistical Life Year We selected two additional VSLYs to simulate: $100,000 and $300,000. These values capture the range of most estimates of VSLY as reported in a widely cited

21 review of the literature on VSLY, after adjusted to 2014 US dollars. 33 Appendix Table 9 below displays the incremental social values at $100,000; $200,000; and $300,000 at each half month PFS benefit threshold from 0 to 3+ months holding other baseline parameters constant. Lowering the VSLY to $100,000 changes the indifference threshold from 1 month to 2.5 months, whereas raising the VSLY to $300,000 changes the indifference threshold from 1 month to 0.5 months. etable 9. Incremental Social Value by PFS Benefit Threshold and Value of a Statistical Life Year PFS benefit >x VSLY $100K VSLY $200K VSLY $300K 0 $327,367 $170,733 $14, $313,731 $143,462 $26,807 1 $205,136 $73,729 $352, $154,125 $175,750 $505,625 2 $154,125 $175,750 $505, $38,353 $560,706 $1,083, $38,353 $560,706 $1,083,059 Treatment Cost As noted above, the values from our literature review on incremental lifetime treatment cost range from $2,000 to $62,000. We calculated incremental social value at each half month PFS threshold using our other baseline parameters with incremental lifetime treatment costs of $2,000; $22,000; and $62,000, as shown in Appendix Table 10 below. Treatment cost is the most sensitive parameter. Increasing treatment cost to $62,000 also increases the PFS benefit threshold to greater than 3 months. Lowering the treatment cost to $2,000 lowers the PFS benefit threshold to 0 months.

22 etable 10. Incremental Social Value by PFS Benefit Threshold and Incremental Lifetime Treatment Cost PFS benefit >x $62K Cost $22K Cost $2K Cost 0 $1,210,996 $170,733 $109, $1,218,537 $143,462 $101,463 1 $1,140,909 $73,729 $179, $1,100,100 $175,750 $219,900 2 $1,100,100 $175,750 $219, $946,118 $560,706 $373, $946,118 $560,706 $373,882 Publication Delay To find additional instances of a single clinical trial with separate PFS and OS publications, we relaxed two restriction criteria: phase 3 trials and publication with Kaplan Meier survival tables. In so doing, we were able to identify four additional paired publications as show in Appendix Table 11 below with publication delay ranging from 7 months to 46 months. etable 11. NSCLC Trials With Separate PFS and OS Publications, PFS Publication Date OS Publication Date Months Delay AVAPERL Jul Feb PARAMOUNT Mar Aug FASTACT Oct Jul NEJ002 Jun Jan Using the baseline model parameters for VSLY and treatment cost, we calculated incremental social value using a seven month publication delay and a 46 month delay. The length of time for the delay between PFS and OS publication does not alter the PFS benefit thresholds, but serves as a multiplier that scales incremental social value up or down, as shown in Appendix Table 12 below.

23 etable 12. Incremental Social Value by PFS Benefit Threshold and Publication Delay PFS benefit >x 7 months 22 months 46 months 0 $54,324 $170,733 $356, $45,647 $143,462 $299,966 1 $23,460 $73,729 $154, $55,920 $175,750 $367,477 2 $55,920 $175,750 $367, $178,406 $560,706 $1,172, $178,406 $560,706 $1,172,385 For VSLY, treatment cost, and publication delay, we also simulated the effect on the PFS benefit threshold when all three parameters were modeled simultaneously using all possible combinations of the low, medium, and high parameter scenarios for VSLY, treatment cost, and publication delay as described in Appendix Table 13 below. etable 13. Parameter Values Used for Sensitivity Analyses VSLY Treatment Cost Months Delay Low Patient Benefit $100,000 $62,000 7 Medium Patient $200,000 $22, Benefit High Patient Benefit $300,000 $2, As indicated in the single parameter sensitivity analyses, treatment cost has the greatest impact on the PFS benefit threshold, while the publication delay has no impact. The PFS benefit thresholds for each combination of parameters can be found below in Appendix Table 14.

24 etable 14. Sensitivity Analysis Scenarios Results Scenario Value of a Statistical Life Year Lifetime Incremental Treatment Cost Delay between PFS and OS publication Indifference Threshold (PFS > X; months) (months) A $100,000 $62, B $100,000 $62, C $100,000 $62, D $100,000 $22, E $100,000 $22, F $100,000 $22, G $100,000 $2, H $100,000 $2, I $100,000 $2, J $200,000 $62, K $200,000 $62, L $200,000 $62, M $200,000 $22, N $200,000 $22, O $200,000 $22, P $200,000 $2, Q $200,000 $2, R $200,000 $2, S $300,000 $62, T $300,000 $62, U $300,000 $62, V $300,000 $22, W $300,000 $22, X $300,000 $22, Y $300,000 $2, Z $300,000 $2, ZA $300,000 $2,

25 Publication Bias and Clinical Uncertainty We returned to the literature to identify three phase 3 publications with published PFS median outcomes, but no OS outcomes. To test the impact of both publication bias and clinical uncertainty, we assumed that the OS outcomes for these three trials was less than or equal to zero and calculated updated probabilities and expected benefits with these three additional trials included. As shown in Appendix Table 15 below, two of the trials had net PFS benefits of greater than 3 months. etable 15. Net PFS Benefits for Clinical Uncertainty Sensitivity Analysis Paper Intervention Drug Comparator Drug B PFS Rosell erlotinib cisplatin + docetaxel (2012) 45 gemcitabine Chang bevacizumab + pemetrexed + cisplatin 1 (2011) 46 cisplatin Chen (2013) 47 erlotinib gemcitabine + carboplatin 9.1 Appendix Table 16 below contains the correlations between PFS and OS and expected benefits as well as the incremental social value at $100K, $200K, and $300K VSLY for each half month PFS benefit threshold. Increasing the clinical uncertainty and accounting for publication bias in this way changed the PFS thresholds for VSLY values of $100K and $200K, but not for $300K.

26 etable 16. Clinical Uncertainty and Publication Bias Sensitivity Analysis Results PFS benefit >x Pr(BOS>0 PFS>x) Pr(BOS<=0 PFS>x) E(BOS BOS>0,P FS>x) E(BOS BOS<0,P FS>x) Incremental social value (VSLY 100K) Incremental social value (VSLY 200K) Incremental social value (VSLY 300K) $(347,175) $(210,350) $(73,525) $(342,415) $(200,829) $(59,244) $(274,852) $(65,704) $143, $(248,375) $(12,750) $222, $(248,375) $(12,750) $222, $(170,588) $142,824 $456, $(170,588) $142,824 $456,235

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