Affiliations of authors: T. T. Chen, R. Simon (Biometric Research Branch, Division of Cancer Treatment and Diagnosis), E. Feigal (Division of Cancer Treatment and Diagnosis), B. E. Johnson (Medicine Branch, Division of Clinical Sciences), National Cancer Institute, Bethesda, MD; J. P. Chute, Division of Hematology/Oncology and the Naval Medical Research Center, National Naval Medical Center, Bethesda.
Correspondence to present address: T. Timothy Chen, Ph.D., Biostatistics Section, University of Maryland Greenebaum Cancer Center, 22 South Greene St., Baltimore, MD 21201 (e-mail: tchen001{at}umaryland.edu).
![]() |
ABSTRACT |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
![]() |
INTRODUCTION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Currently, phase II studies use response rate, not survival, as the major end point; however, in the case of phase II trials for patients with extensive-stage SCLC, survival data have usually been collected before a phase III trial is initiated. We believe that survival data from phase II studies of extensive-stage SCLC can be better utilized to help decide which regimens should be brought to phase III trial.
We have developed a statistical model based on our National Cancer Institute (NCI) intramural experience (2), on extramural phase II studies, and on data from the North American cooperative groups' randomized phase III trials for patients with extensive-stage SCLC performed over a 22-year period (1). The time period from 1972 through 1990 was chosen because it includes the time of the introduction of combination chemotherapy and allows the passage of enough time so that the survival data are mature and nearly all of the studies have been published. This model was developed so that clinical researchers can use the survival data from a phase II study to help predict whether their new regimen is likely to increase the survival of patients with extensive-stage SCLC compared with standard chemotherapy regimens in a prospective trial. In this report, we provide evidence that this model offers a potential tool for clinicians to assess the likelihood that a phase II chemotherapy regimen will prove superior to standard regimens when applied in a phase III trial for extensive-stage SCLC.
![]() |
METHODS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
The phase III trials initiated during the period from 1972 through 1990 for patients with extensive-stage SCLC were identified through a search of the database of the Cancer Therapy Evaluation Program, NCI, Bethesda, MD. A review of these studies was recently published (1).
Phase II Trials
For each published phase III trial of patients with extensive-stage SCLC, we attempted to identify a phase II study that preceded the randomized trial. Phase II studies were initially identified through a review of published references. The authors and chairpersons of the lung cancer committee of the cooperative groups that published these studies were then contacted if possible to confirm that the phase II study we identified was the one that gave rise to the randomized phase III trial. Information was obtained on the dates of the phase II studies, the number and sex of patients, the treatment regimens, the response rates, the median survival, and the number of patient deaths at the time of the phase II analysis. We included only phase II studies that were performed by the cooperative group that conducted the subsequent phase III trial, that were performed at an institution that was a participating member of the subsequent phase III trial, or that were performed at a single institution using a regimen analogous to that tested in a subsequent cooperative group trial. We classified the phase II and phase III trials on the basis of whether they were initiated before or up through 1981. We chose this division because it was an approximate midway time point, and it coincides with the transition from cyclophosphamide-based to cisplatin-based chemotherapy at our own institutions and by the cooperative groups (1,2).
We have plotted the phase II median survival (Fig. 1, A) and response rate (Fig. 1
, B) versus the median survival of patients treated on the experimental arm of the subsequent phase III trials. The ordinary least-squares regression lines are calculated and drawn on both panels of Fig. 1
.
|
The statistical power of a phase III clinical trial is the probability of obtaining a statistically significant result. Statistical power calculations are usually based on assumed distributions of survival for the control and experimental regimens, with the medians specified. For example, one might assume that the distributions of survival are exponential in form, with a 9-month median for the control group and a 12-month median for the experimental group. The specification of the median for the control group is usually based on data from previous phase III trials using the control or current regimen. The median for the experimental group, however, is usually hypothetical. The experimental median usually represents the smallest anticipated medically significant improvement in survival over current therapy. This anticipated median survival is used to help determine the number of patients needed for the required statistical power.
In our model, survival data from the phase II study of the experimental regimen are used to calculate the expected power of the phase III trial. The subscript c represents the control values, and the subscript e represents the experimental values throughout. P (c ,
e , d) denotes the statistical power of a phase III trial comparing a control treatment with an exponential distribution of survival duration with a failure rate
c versus an experimental treatment with an exponential distribution of survival with a failure rate
e when a total of d deaths will be observed in the phase III trial. The exponential distribution has a constant hazard rate by definition, and this distribution assumption is appropriate in our situation. We assume statistical significance when a two-tailed test results in P<.05. Expected power is defined as the average value of P (
c ,
e , d ) with regard to the distributions of
c and
e that are expected on the basis of available data.
At the time of planning a phase III trial, our model requires that information about c be specified as a gamma probability distribution, as is conventional for Bayesian analysis with exponential distributions. The model uses Bayesian analysis as a way to incorporate information about the effectiveness of an experimental treatment into the planning of a phase III trial (3). This information can be formally modeled and used in the computation of the expected power of a phase III trial. The gamma distribution has two parameters, ac and bc. The parameter ac represents the amount of information (number of deaths) on which the prior distribution is based and is assumed to be a fixed number. The parameter 1/bc represents the total patient-years of survival (until death or censoring) in previous experience with the treatment and is derived so that the median survival is at a specified value. (Equivalently, given ac and median survival, we calculate bc.)
The statistical analysis takes into account the evidence of increases in median survival for control treatments over time. The distribution of exponential failure rates for arms of phase III trials initiated from 1972 through 1981 were well represented by a gamma distribution with parameters ac = 136 and 1/bc = 1380, corresponding to a median survival of approximately 7.0 months. For control arms of trials initiated after 1981, the distribution was well represented using ac =136 and 1/bc = 1741, corresponding to a median survival of approximately 8.9 months.
Information about the failure rate for the experimental treatment e available at the time of planning the phase III trial can also be specified as a gamma probability distribution. Before the phase II study of the experimental regimen, we specified our prior distribution by determining ae and be to give an expected median (me) approximately equal to that expected for the control treatment but with the probability .20 that me is greater than 12 months. We used ae = 10 and 1/be = 125. These values can be considered realistic approximations because fewer than 20% of past experimental regimens have yielded medically important improvements.
The parameters specified above as representing expectations for the experimental regimen prior to conducting a phase III trial are updated in the model based on phase II results in the following way: At the time of planning a phase III trial, ae = 10 + de, where de is the number of deaths observed in the phase II trial, and 1/be = 125 + Te, where Te is the sum of the survival times in months (until death or last follow-up) observed for patients in the phase II trial. These simple updating rules are a result of the complementarity of the exponential distribution of survival and the gamma prior distribution of the hazard parameter.
These specifications permit us to compute the expected power of a phase III trial following a particular phase II study. For the log-rank test with exponential survivals of moderate-sized treatment effects, the power for specific values of c and
e can be approximated by
![]() | (1) |
where F-1 is the inverse of the standard normal distribution function, z1 - a/2 is the upper 100(1 -a/2) percentile of the normal distribution, and d is the total number of deaths expected in the phase III trial at the time of analysis. To compute expected power, we averaged this quantity with regard to the gamma distributions of c and
e described above. We used d = 256 as the total number of deaths to be observed in a phase III trial, corresponding to a 90% statistical power for detecting a 50% increase in median survival with a two-sided 5% significance level. The averages were approximated by Monte Carlo integration with 10 000 samples.
![]() |
RESULTS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Twenty-one North American cooperative group phase III trials of chemotherapy regimens for extensive-stage SCLC were identified that were initiated during the period from 1972 through 1990 and for which the results have been published (1,424). Only five (24%) of the 21 trials demonstrated a statistically significant difference between the experimental treatment arm and the standard treatment arm. These five studies revealed a statistically significant trend toward an increase in overall patient survival. The median survival of patients treated on the control arm was 7.0 months for studies started during the period from 1972 through 1981; it was 8.9 months for studies started during the period from 1982 through 1990 (P = .001).
Phase II Studies
We identified nine phase II studies (2533) that tested a regimen subsequently studied in a phase III trial (1). The information from these phase II studies is summarized in Table 1. We excluded the other 12 phase III trials (1) because we found differences in either the chemotherapeutic drugs used or the chemotherapy schedule between the phase II regimens cited as the basis for the phase III trials and the phase III trials performed (47,9,10,12,13,116,18,20,23).
|
Response rates are frequently used to assess the likelihood that a phase II regimen will increase survival over standard treatment in a phase III trial. For eight of the nine phase II trials, response rates were available and these were compared with the survival observed in the subsequent phase III trials. Fig. 1, B, shows that the response rates in the phase II studies did not correlate with the median survival of patients treated with a particular regimen in the subsequent phase III trial. The least-squares regression line is given in the figure, and the Pearson correlation coefficient is .13 (P = .67). To give one example of this poor correlation, 95% of the patients treated on the phase II study by Natale et al. (30) showed a partial or a complete response (Table 1
); however, in the subsequent phase III study, patients receiving the same experimental regimen had a median survival duration of only 8.1 months.
Since response rates in phase II trials have a poor correlation with the phase III survival results, our predictive model utilizes the survival information instead of response rates. To retrospectively test how well the statistical model estimates the outcome of the phase III trials from phase II survival data, we analyzed the nine phase II studies that gave rise to subsequent phase III trials of the same regimen. In Table 2, the results (median survival and number of deaths) of the nine phase II studies and the expected power of each corresponding phase III study as obtained from the model are shown. The expected power is the usual statistical power averaged with regard to the size of the treatment difference anticipated on the basis of the median survival observed in the phase II trial, the number of deaths observed in the phase II trial, and the distribution of median survivals expected in the phase III trial for the control treatment.
|
The other seven phase II trials had expected powers ranging from 0.19 to 0.52, and six (86%) of the seven subsequent phase III trials showed no difference between the survival of patients on the experimental arm and that of patients on the standard arm (1). The exception was the phase II regimen developed by Loehrer et al. (32), which gave an expected power of 0.21, but the subsequent phase III trial showed a statistically significant difference between the survival of patients treated on the experimental arm and that of patients treated on the standard arm (P = .044; median survival = 9.1 months versus 7.3 months). However, this phase III trial by Loehrer et al. (22) may be a poor example to compare with the power estimate of the model because the median survival of patients on the control arm (7.3 months) is lower than what has been observed in most other studies conducted after 1981.
To illustrate how expected power can be determined from future phase II trials, Fig. 2 reflects the decade of treatment up through 1981 (Fig. 2
, A) and the decade after 1981 (Fig. 2
, B). The two panels of this figure show expected power as a function of median survival observed in the phase II trial. The different lines correspond to different numbers of deaths (events) observed in the phase II trial. The computations assume that the phase III trial will be sized to include 256 deaths (300 patients followed for 3 years; 150 patients on each arm). To apply to the nine phase II trials retrospectively, three phase II studies up through 1981 are represented in Fig. 2
, A, and six phase II studies identified after 1981 are represented in Fig. 2
, B.
|
![]() |
DISCUSSION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
We identified nine phase II studies of treatment regimens that corresponded with nine subsequent phase III trials initiated in North America during the period from 1972 through 1990 (Table 1). We developed a model in this report and retrospectively applied our model to these nine phase II studies. Our analysis indicates that an expected power of greater than 0.55 for a particular phase II study appears to be a reasonable reference point toward estimating that the regimen is likely to statistically significantly prolong survival when compared with standard treatment in a phase III trial. Our analysis showed that a high expected power generated by the model (>0.55) was associated with a higher likelihood that an experimental regimen would increase survival relative to the standard regimen. However, promising results from a phase II trial are rarely sufficient to establish the superiority of a new regimen in the absence of a confirmatory phase III trial. Conversely, a low expected power (
0.55) scored for a particular phase II regimen does not necessarily predict that the regimen will not prolong survival compared with standard treatment in a phase III trial. Indeed, one phase II regimen with an expected power of less than 0.55 increased survival statistically significantly in the subsequent phase III trial.
Although the initial application of our model toward estimating phase III results from phase II studies of extensive-stage SCLC appears promising, the use of historical data to predict the efficacy of a particular treatment poses several problems. Differences in patient selection, treatment regimens, and supportive care are unaccounted for when a current treatment regimen is compared with historical data based on previous regimens. Indeed, for patients with extensive-stage SCLC, it has been demonstrated that the number of women enrolled in a clinical trial, the use of cisplatin-based regimens, and improved supportive care may each have an impact on patient outcomes over time (1,2,3537). Therefore, a historical database that includes 22 years of different clinical trials may include artifacts that render the database invalid for the generation of a model. However, neither sex nor cisplatin-containing regimens had an independent, statistically significant impact on patient survival in our historical database. Therefore, we believe that the database we have used to generate our model is a valid comparison group against which to compare future phase II regimens for extensive-stage SCLC. Nevertheless, individual cooperative groups could use values of ac and bc representative of their own phase III control group experiences for use with this model. To model a particular trial in which the median survival for the control group was mc with d deaths, we set ac = d and determine the value bc numerically. We have also applied our approach to obtain a predictive model for limited-stage SCLC (38). For diseases such as leukemia, whose survival cannot be adequately approximated by exponential distributions, the method described here requires extension to take care of possible cure in the survival distribution.
The use of the model described herein has implications for the future design of phase II trials. As we have illustrated in Fig. 2, panels A and B, the expected power to predict whether a regimen that appears promising in a phase II trial will be successful in a phase III trial depends on the number of deaths observed in the phase II trial and the median survival observed. For example, consider a phase II study with 50 deaths observed with a median survival of 14 months. The expected power of the subsequent phase III trial is 0.80 (taken from Fig. 2
, B). In contrast, if 10 deaths are observed, with a median survival of 14 months, the expected power is 0.57. Equation 1 or Fig. 2
, panels A and B, can be used to obtain the number of deaths required in the phase II trial. However, it can be seen from Fig. 2
, A and B, very small phase II trials (fewer than 25 patients) provide an inadequate basis for evaluating the applicability to a phase III trial of survival results that may appear promising in a phase II trial. In our study, we found that the total number of patients in all nine phase II studies is only 265. This finding indicates that, up to 1990, the phase II trials were designed with inadequate size. The situation is different today because of the utilization of an optimal two-stage or three-stage design to differentiate the specified desirable and undesirable response rates (39,40).
The validity of our statistical model and its usefulness in assessing experimental treatment regimens for patients with extensive-stage SCLC can be verified only through future prospective studies. Our results thus far suggest that a particular phase II regimen with an expected power of greater than 0.55 provides a reasonable basis for a subsequent phase III evaluation of the regimen. The use of this model may expedite the randomized study of regimens that show promise in phase II studies and would give pause to researchers prior to conducting a phase III trial if the model results suggest that the experimental regimen will be unlikely to prolong survival compared with standard therapy.
![]() |
NOTES |
---|
Present address: B. E. Johnson, Lowe Center for Thoracic Oncology, Department of Adult Oncology, Dana Farber Cancer Institute, Boston, MA.
![]() |
REFERENCES |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
1
Chute JP, Chen TT, Feigal E, Simon R, Johnson BE. Twenty years of phase III trials for patients with extensive-stage small-cell lung cancer: perceptible progress. J Clin Oncol 1999;17:1794801.
2 Chute JP, Venzon DJ, Hankins L, Okunieff P, Frame JN, Ihde DC, et al. Outcome of patients with small-cell lung cancer during 20 years of clinical research at the US National Cancer Institute. Mayo Clin Proc 1997;72:90112.[Medline]
3 Carlin BP, Louis TA. Bayes and empirical Bayes methods for data analysis. London (U.K.): Chapman & Hall; 1996.
4 Maurer LH, Tulloh M, Weiss RB, Blom J, Leone L, Glidewell O, et al. A randomized combined modality trial in small cell carcinoma of the lung: comparison of combination chemotherapyradiation therapy versus cyclophosphamideradiation therapy effects of maintenance chemotherapy and prophylactic whole brain irradiation. Cancer 1980;45:309.[Medline]
5 Ettinger DS, Lagakos S. Phase III study of CCNU, cyclophosphamide, adriamycin, vincristine, and VP-16 in small-cell carcinoma of the lung. Cancer 1982;49:154454.[Medline]
6 Lowenbraun S, Bartolucci A, Smalley RV, Lynn M, Krauss S, Durant JR. The superiority of combination chemotherapy over single agent chemotherapy in small cell carcinoma. Cancer 1979;44:40613.[Medline]
7 McCracken JD, Heilbrun L, White J, Reed R, Samson M, Saiers JH, et al. Combination chemotherapy, radiotherapy, and BCG im-munotherapy in extensive (metastatic) small cell carcinoma of the lung. A Southwest Oncology Group study. Cancer 1980;46:2335 40.[Medline]
8 Daniels JR, Chak LY, Sikic BI, Lockbaum P, Kohler M, Carter SK, et al. Chemotherapy of small-cell carcinoma of lung: a randomized comparison of alternating and sequential combination chemotherapy programs. J Clin Oncol 1984;2:11929.[Abstract]
9 Livingston RB, Mira JG, Chen TT, McGavran M, Costanzi JJ, Samson M. Combined modality treatment of extensive small cell lung cancer: a Southwest Oncology Group study. J Clin Oncol 1984;2:58590.[Abstract]
10 Sandler A, Jiroutek M, Vogl S, Johnson D. A comparison of standard with intensive combination chemotherapy in small cell lung cancer, mature results: an Eastern Cooperative Oncology Group trial (ECOG) [abstract]. Proc ASCO 1997;16:418a.
11 Jackson DV Jr, Case LD, Zekan PJ, Powell BL, Caldwell RD, Bearden JD, et al. Improvement of long-term survival in extensive small-cell lung cancer. J Clin Oncol 1988;6:11619.[Abstract]
12 Everson LK, Jett JR, O'Fallon JR, Krook JE, Dalton RJ, Mailliard JA, et al. Alternating chemotherapy with or without VP-16 in extensive-stage small-cell lung cancer. Am J Clin Oncol 1989;12:33944.[Medline]
13 Hong WK, Nicaise C, Lawson R, Maroun J, Comis R, Speer J, et al. Etoposide combined with cyclophosphamide plus vincristine compared with doxorubicin plus cyclophosphamide plus vincristine and with high-dose cyclophosphamide plus vincristine in the treatment of small-cell carcinoma of the lung: a randomized trial of the Bristol Lung Cancer Study Group. J Clin Oncol 1989;7:4506.[Abstract]
14 Chahinian AP, Propert KJ, Ware JH, Zimmer B, Perry MC, Hirsh V, et al. A randomized trial of anticoagulation with warfarin and of alternating chemotherapy in extensive small-cell lung cancer by the Cancer and Leukemia Group B. J Clin Oncol 1989;7:9931002.[Abstract]
15 Johnson DH, Einhorn LH, Birch R, Vollmer R, Perez C, Krauss S, et al. A randomized comparison of high-dose versus conventional-dose cyclophosphamide, doxorubicin, and vincristine for extensive-stage small-cell lung cancer: a phase III trial of the Southeastern Cancer Study Group. J Clin Oncol 1987;5:17318.[Abstract]
16 Evans WK, Feld R, Murray N, Willan A, Coy P, Osoba D, et al. Superiority of alternating non-cross-resistant chemotherapy in extensive small cell lung cancer. A multicenter, randomized clinical trial by the National Cancer Institute of Canada. Ann Intern Med 1987;107:4518.[Medline]
17 Ettinger DS, Finkelstein DM, Abeloff MD, Ruckdeschel JC, Aisner SC, Eggleston JC. A randomized comparison of standard chemotherapy versus alternating chemotherapy and maintenance versus no maintenance therapy for extensive-stage small-cell lung cancer: a phase III study of the Eastern Cooperative Oncology Group. J Clin Oncol 1990;8:23040.[Abstract]
18 Livingston RB, Schulman S, Mira JG, Harker G, Vogel S, Coltman CA Jr, et al. Combined alkylators and multiple-site irradiation for extensive small cell lung cancer: a Southwest Oncology Group Study. Cancer Treat Rep 1986;70:1395401.[Medline]
19 Roth BJ, Johnson DH, Einhorn LH, Shacter LP, Cherng NC, Cohen HJ, et al. Randomized study of cyclophosphamide, doxorubicin, and vincristine versus etoposide and cisplatin versus alternation of these two regimens in extensive small-cell lung cancer: a phase III trial of the Southeastern Cancer Study Group. J Clin Oncol 1992;10:28291.[Abstract]
20 Ettinger DS, Finkelstein DM, Abeloff MD, Skeel RT, Stott PB, Frontiera MS, et al. Justification for evaluating new anticancer drugs in selected untreated patients with extensive-stage small-cell lung cancer: an Eastern Cooperative Oncology Group randomized study. J Natl Cancer Inst 1992;84:107784.[Abstract]
21 Maksymiuk AW, Jett JR, Earle JD, Su JQ, Diegert FA, Mailliard JA, et al. Sequencing and schedule effects of cisplatin plus etoposide in small-cell lung cancer: results of a North Central Cancer Treatment Group randomized clinical trial. J Clin Oncol 1994;12:706.[Abstract]
22 Loehrer PJ Sr, Ansari R, Gonin R, Monaco F, Fisher W, Sandler A, et al. Cisplatin plus etoposide with and without ifosfamide in extensive small-cell lung cancer: a Hoosier Oncology Group study. J Clin Oncol 1995;13:25949.[Abstract]
23 Rowland KM Jr, Loprinzi CL, Shaw EG, Maksymiuk AW, Kuross SA, Jung SH, et al. Randomized double-blind placebo-controlled trial of cisplatin and etoposide plus megestrol acetate/placebo in extensive-stage small-cell lung cancer: a North Central Cancer Treatment Group study. J Clin Oncol 1996;14:13541.[Abstract]
24 Miller AA, Herndon JE 2nd, Hollis DR, Ellerton J, Langleben A, Richards F 2nd, et al. Schedule dependency of 21-day oral versus 3-day intravenous etoposide in combination with intravenous cisplatin in extensive-stage small-cell lung cancer: a randomized phase III study of the Cancer and Leukemia Group B. J Clin Oncol 1995;13:18719.[Abstract]
25 Williams C, Alexander M, Glatstein EJ, Daniels JR. Role of radiation therapy in combination with chemotherapy in extensive oat cell cancer of the lung: a randomized study. Cancer Treat Rep 1977;61:142731.[Medline]
26 Messeih AA, Schweitzer JM, Lipton A, Harvey HA, Simmonds MA, Stryker JA, et al. Addition of etoposide to cyclophosphamide, doxorubicin, and vincristine for remission induction and survival in patients with small cell lung cancer. Cancer Treat Rep 1987;71:616.[Medline]
27 Zacharski LR, Henderson WG, Rickles FR, Forman WB, Cornell CJ Jr, Forcier RJ, et al. Effect of warfarin on survival in small cell carcinoma of the lung. Veterans Administration Study No. 75. JAMA 1981;245:8315.[Abstract]
28 Lowenbraun S, Birch R, Buchanan R, Krauss S, Durant J, Perez C, et al. Combination chemotherapy in small cell lung carcinoma. A randomized study of two intensive regimens. Cancer 1984;54:234450.[Medline]
29 Markman M, Abeloff MD, Berkman AW, Waterfield WC. Intensive alternating chemotherapy regimen in small cell carcinoma of the lung. Cancer Treat Rep 1985;69:1616.[Medline]
30 Natale RB, Shank B, Hilaris BS, Wittes RE. Combination cyclophosphamide, Adriamycin, and vincristine rapidly alternating with combination cisplatin and VP-16 in treatment of small cell lung cancer. Am J Med 1985;79:3038.[Medline]
31 Krook JE, Jett JR, Little C. A phase III study of sequential infusion VP-16 and cisplatin therapy in advanced lung cancer. Am J Clin Oncol 1989;12:1147.[Medline]
32 Loehrer PJ Sr, Rynard S, Ansari R, Songer J, Pennington K, Einhorn L. Etoposide, ifosfamide, and cisplatin in extensive small cell lung cancer. Cancer 1992;69:66973.[Medline]
33 Murphy PB, Hainsworth JD, Greco FA, Hande KR, DeVore RF, Johnson DH. A phase II trial of cisplatin and prolonged administration of oral etoposide in extensive-stage small cell lung cancer. Cancer 1992;69:3705.[Medline]
34 Chen, TT. Statistical aspects of cancer clinical trials. In: Buncher CR, Tsay JY, editors. Statistics in the pharmaceutical industry. 2nd ed. New York (NY): Marcel Dekker; 1994. p. 14363.
35 Albain KS, Crowley JJ, LeBlanc M, Livingston RB. Determinants of improved outcome in small-cell lung cancer: an analysis of the 2,580-patient Southwest Oncology Group data base. J Clin Oncol 1990;8:156374.[Abstract]
36 Spiegelman D, Maurer LH, Ware JH, Perry MC, Chahinian AP, Comis R, et al. Prognostic factors in small-cell carcinoma of the lung: an analysis of 1,521 patients. J Clin Oncol 1989;7:34454.[Abstract]
37 Dearing MP, Steinberg SM, Phelps R, Anderson MJ, Mulshine JL, Ihde DC, et al. Outcome of patients with small-cell lung cancer: effect of changes in staging procedures and imaging technology on prognostic factors over 14 years. J Clin Oncol 1990;8:10429.[Abstract]
38 Janne PA, Freidlin B, Saxman S, Johnson BE. The survival of patients treated for limited stage small cell lung cancer has increased during the past 20 years [abstract]. In: Proceedings of the 9th World Conference on Lung Cancer 2000;21 [abstract 3484]. Lung Cancer 2000;29:August.
39 Simon R. Optimal two-stage designs for phase II clinical trials. Controlled Clin Trials 1989;10:110.[Medline]
40 Chen TT. Optimal three-stage designs for phase II cancer clinical trials. Stat Med 1997;16:270111.[Medline]
Manuscript received December 22, 1999; revised July 19, 2000; accepted July 26, 2000.
This article has been cited by other articles in HighWire Press-hosted journals:
![]() |
||||
|
Oxford University Press Privacy Policy and Legal Statement |