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Selection of Active Drugs for Ovarian Cancer Based on CA-125 and Standard Response Rates in Phase II Trials

From the Cancer Treatment Centreand Gray Laboratory, Mount Vernon Hospital, Northwood, Middlesex; and Orchard Farmhouse, Back Lane, Roughton, Norfolk, United Kingdom.

Address reprint requests to Gordon J.S. Rustin, MD, FRCP, Cancer Treatment Centre, Mount Vernon Hospital, Northwood, Middlesex, HA6 2RN, United Kingdom; email rustin{at}mtvern.co.uk

	ABSTRACT

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION APPENDIX Statistical Method REFERENCES

 
PURPOSE: To determine whether precise definitions of response based on serial CA-125 levels can predict the activity of drugs in phase II trials for ovarian cancer as accurately as standard criteria.

PATIENTS AND METHODS: Fourteen different drugs for relapsed ovarian cancer were analyzed in 25 treatment groups in 19 clinical trials. Response rates were estimated in 1,457 assessable patients according to standard criteria and in 1,092 assessable patients according to CA-125. For each drug trial, the observed response rates acted as the input data for an evaluation of how the two criteria would perform in a hypothetical Gehan two-stage phase II trial, accepting a target drug efficacy rate of 20% and a rejection error of 5%.

RESULTS: CA-125 and clinical response criteria were concordant in 20 of the 25 groups, with less than 5% chance of rejecting the drug in nine groups and greater than 5% in 11 groups. In four groups, the drug had less than 5% chance of being rejected by CA-125 but greater than 5% chance of being rejected by standard criteria. The difference in the classification of drugs by the standard and CA-125 response criteria was not statistically significant (P = .38, McNemar’s test). CA-125 response rates were slightly higher than standard response rates by a factor of 1.11.

CONCLUSION: Definitions based on a 50% or 75% decrease of CA-125 levels accurately predicted which drugs in phase II trials for relapsed ovarian cancer were active and justified further investigation.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION APPENDIX Statistical Method REFERENCES

 
ALMOST THREE QUARTERS of women diagnosed as having ovarian carcinoma are given chemotherapy and yet die from their disease. Better drugs are required for the treatment of this condition. Response rates are a major end point used in clinical trials to assess the activity of new drugs. However, in a substantial proportion of patients with ovarian carcinoma, the disease cannot be adequately monitored by computed tomography or ultrasound scans because the typical cancer nodules on the bowel or peritoneum cannot be adequately visualized. Fortunately, more than 90% of these women have an elevated serum CA-125 level.¹ Decreasing levels have been shown to be associated with response to therapy.^1,2 To prove that response rates according to CA-125 are as reliable as response rates according to standard criteria, requires that clear definitions based on CA-125 are compared with standard response criteria, such as those proposed by the World Health Organization or Eastern Cooperative Oncology Group.^3,4

Definitions based on a 50% or 75% decrease of CA-125 have recently been shown to reliably define response of ovarian cancer in patients receiving first-line chemotherapy.⁵ A major use for response rates is in determining the activity of drugs in phase II trials. Therefore, we have evaluated the application of the standard and CA-125 response criteria in the screening of 14 different drugs for efficacy against ovarian cancer. This paper studies the use of CA-125 in clinical trials to score patients as responders or nonresponders. This must be distinguished from individual patient management where a serial increase or decrease of CA-125 can be used in conjunction with signs, symptoms, or scans to impact on therapy.⁶

	PATIENTS AND METHODS

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION APPENDIX Statistical Method REFERENCES

 
Patients
Coordinators of clinical trials of a range of cytotoxic drugs for relapsed ovarian carcinoma were approached. All clinical trials were performed after approval of the protocol by a local institutional review board. If CA-125 was regularly measured as part of the trial protocol, the trial coordinators were requested to make available appropriate data. These included the date the trial treatment started, the date and value of each CA-125 measurement, the best response and date of best response according to the locally used standard criteria, the date of progression, and the date of last contact or death. Details of the phase II trials are listed in Table 1. Response rates according to standard criteria were measured in 1,457 assessable patients, and 1,092 patients were assessable according to CA-125 criteria. Twelve patients in the altretamine trial, 12 in the EORTC docetaxel trials, and 16 in the isotretinoin/calcitriol trials were included despite having no clinically assessable disease, but they were assessed regularly for clinical progression. Because eligibility criteria for the other trials included assessable disease according to standard criteria but not an elevated CA-125 level, many patients were assessable according to standard criteria but not CA-125 criteria.

A biologic response based on CA-125 was defined as either a 50% or a 75% reduction in CA-125 levels. To reduce the chance of falsely predicting a response, the 50% CA-125 response definition required four CA-125 levels, two initial elevated samples and the sample showing a 50% decrease requiring confirmation by a fourth sample. The 75% CA-125 response definition required only three CA-125 levels, with a serial decrease of at least 75%. In both 50% and 75% response definitions, the final sample has to be at least 28 days after the previous sample.

Statistical Methods
Most phase II studies of cancer drugs have a so-called two-stage design. The classical design is the Gehan two-stage design, in which the initial screen for efficacy is performed in a relatively small series of patients, typically less than 20.⁷ If no objective response is seen in any of these patients, the drug is rejected as being less efficient than some chosen threshold efficacy. A drug producing one or more responses among this first series of patients will enter the second stage, in which an additional 20 to 30 patients are typically treated with the drug. The purpose of this second stage is to estimate the response rate with a desired level of statistical precision. However, even a drug with a real efficacy above the threshold value will have a chance of being rejected in the first stage, a so-called rejection error. Conventionally, the rejection error is chosen at 5% when designing a study. There are more elaborate versions of the Gehan design, but for the sake of simplicity, we will treat only the classical design here.

To design a specific trial according to Gehan’s idea, the target drug efficacy must be chosen. In this evaluation, we chose 20%; ie, we will estimate the number of patients needed in the first stage of a phase II study so that a drug with a 20% efficacy has a less than 5% chance of being rejected as inefficient. The calculation is straightforward; a 20% efficacy means that the probability of a patient not responding is .8. The probability that none out of m patients responds to the drug is then P_rej = .8^m. For a 5% rejection error, we simply need to determine m so that .8^m .05. For m = 14, the rejection probability for a drug with 20% efficacy is 4.4%, and for m = 13, it is 5.5%. Therefore, the first stage of the trial designed under the above assumptions should include 14 patients.

For the 19 phase II studies included here, the clinical and CA-125 response rates are observed. From these, it is possible to estimate the rejection probability for a drug by assuming the observed response rate is a sufficiently accurate estimate of the true efficacy. This assumption breaks down when we only have a small sample of patients, such as the first stage of the Gehan two-stage design. For example, assume that a drug produced zero responses among six treated patients. Clearly, such an observation most likely indicates a drug with a relatively low efficacy. Yet, drugs with a 10% or even a 20% true efficacy would have a reasonable chance of producing zero out of six responses. Such a drug would, of course, have a certain chance of producing one or more responses if another 14 patients were to be treated with the drug. To arrive at a more realistic estimate of the rejection probability, this effect has to be taken into account. Essentially, this is done by estimating the rejection probability averaged over all possible a priori values of the unknown true efficacy of the drug. The mathematical details of this method are presented in the Appendix.

In the second stage of the phase II study, the aim is to use response rates to estimate efficacy with a greater statistical precision. If CA-125 is to be used in place of the standard criteria, then their response rates should be roughly equal. This can be assessed by plotting the standard criteria response rates against the CA-125 criteria response rates. To quantify the concordance between the two response rates, we performed linear regression of observed standard versus CA-125 response frequencies and test if the slope could have a value of 1.

	RESULTS

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION APPENDIX Statistical Method REFERENCES

 
The number of assessable patients in each trial and the response rates are listed in Table 1. The individual drug trials were classified according to rejection errors in the first stage of a Gehan two-stage phase II study using clinical and biochemical response criteria. The relationship between rejection probabilities according to both response criteria in individual trials is shown in Fig 1. The CA-125 and clinical response criteria were concordant in 20 of the 25 groups, with a less than 5% chance of rejecting the drug in nine groups and a greater than 5% in 11 groups (Table 2). In four of the remaining groups, the drug had a less than 5% chance of being rejected by CA-125 but a more than 5% chance of being rejected by standard criteria. In only one group (etoposide trial), the drug was above the 5% threshold by CA-125 (5.8%) but not by standard criteria. The difference in the classification of drugs by the standard and CA-125 response criteria were not significant (P = .38, McNemar’s test, Table 2). The rejection probability may be seen as indicating an active or inactive drug if there is less than or more than 5% probability of rejecting the drug in the first stage of the trial, respectively. We can also estimate the sensitivity and specificity of the CA-125 response criteria for identifying active drugs. The sensitivity is 90% (95% confidence limits, 56%, 100%), and the specificity is 73% (95% confidence limits, 45%, 92%).

View larger version (28K): [in this window] [in a new window]   Fig 1. The relationship between rejection errors according to standard (clin) and CA-125 response criteria in individual trials.

View larger version (28K): [in this window] [in a new window]   Fig 2. The relationship between standard and CA-125 response rates.

	DISCUSSION

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION APPENDIX Statistical Method REFERENCES

 
The main use of response rates in clinical trials is to decide whether a drug is active and worth further studies, whether it is totally inactive and not worth pursuing, or whether it is of marginal activity and its further development depends on a variety of factors, including toxicity. The minimal level of response rate that suggests that a drug is active is usually considered to be 20%, which was the target drug efficacy rate that we used to compare CA-125 with standard response criteria. However, in patients with ovarian cancer that progressed during or within 3 months of initial platinum-based therapy, a lower response rate could still indicate an active drug.⁸ Therefore, we repeated the comparison of CA-125 with standard response criteria for a target efficacy of 10%. Because most of the drugs considered in the present analysis did show some activity in ovarian cancer, relatively fewer would be rejected in a phase II study screening for less than 10% efficacy in the first stage.

The only trial in which patients were split into groups according to time to progression was the European Organization for Research and Treatment of Cancer docetaxel trial.^9,10 There was a progressively greater response rate dependent upon the treatment-free interval measured by either clinical or CA-125 criteria. Apart from the altretamine trial,¹¹ in which all patients had at least a 6-month platinum-free interval, the other studies included patients with a variable mixture of platinum-refractory and -sensitive tumors. It was concluded from the trials of fosquidone,¹² rhizoxin,¹³ tallimustine (R. Savoldelli, personal communication, March, 1996), and raltitrexed¹⁴ that these drugs were inactive with clinical response rates of 0% to 12%. The CA-125 responses ranged from 0% to 14%. Although the CA-125 response rates would also indicate that these drugs are inactive, there were insufficient CA-125 assessable patients in three of these trials to conclude with more than 95% confidence that the response rates were less than 20%.

The response rates according to CA-125 seem to be slightly higher than the standard response rates. For example, a standard response rate of 20% equates to a CA-125 response rate of 22%. However, we would not recommend routine application of a correction factor because this was not statistically significantly different from 1. Response rates were so similar that either standard or CA-125 response criteria could be used in clinical trials.

To understand the statistical approach we used, it may be illustrative to look at a couple of concrete examples. In a Japanese docetaxel study (Katsumata et al, manuscript submitted for publication), clinical response was seen in 17 (28%) of 60 patients. In this case, there is a 1.4% calculated probability that the drug will be rejected in the first stage of a phase II study with 14 patients. The CA-125 response rate was slightly lower (24%), but this estimate was also more uncertain because the total number of patients was 34, eight of whom responded. In this case, the CA-125 rejection probability was 3.4%. Another example is the fosquidone study, where clinical response was seen in zero of 15 patients and CA-125 response in zero of six patients. In both cases, the observed response rate is 0%, but because zero responses among 15 patients is a stronger suggestion of a low efficacy of the drug, the rejection probability is 53% for the clinical response rate compared with 33% for the CA-125 response rate.

The patients in all these trials, except the altretamine trial¹¹ and the isotretinoin/calcitriol trial¹⁵ were selected to have assessable disease according to standard criteria. Although it is possible that such disease may respond differently to chemotherapy than disease that can only be evaluated by CA-125, results from two studies indicate there is no difference. There were 57 assessable patients in the altretamine trial; 45 of the patients were assessable according to European Organization for Research and Treatment of Cancer criteria and 51 according to CA-125 criteria, yet the response rates were identical. In a study of initial chemotherapy, the response rate according to CA-125 was 66% among all 317 CA-125–assessable patients and 67% in those 221 patients who were not assessable according to Gynecologic Oncology Group criteria.⁵

There have been some reports suggesting that CA-125 is unreliable for assessing response of ovarian cancer. However, a recent analysis of 625 patients receiving platinum-based therapy and 144 patients receiving paclitaxel showed that our precise CA-125 criteria were as accurate as standard criteria for assessing response.¹⁶ The use of less precise criteria can be misleading; in a study of fluorouracil the authors stated that CA-125 greatly overestimated the response rate, yet using our CA-125 criteria, the response rate would have been 0.¹⁷

The results presented in this article suggest that future phase II trials of ovarian cancer should be designed so that patients can be entered with either assessable disease according to standard criteria or with elevated CA-125 levels. If 15 U/mL is the lowest accepted limit of accuracy for CA-125, patients need to have levels 60 U/mL to be assessable. This is the lowest level of CA-125 that can be accepted by our criteria for a 75% response. To exclude the possibility of nontumor causes of CA-125 elevation, patients should have a serial increase of at least two levels to 60 U/mL to be assessable according to CA-125. The response rate should be estimated as the sum of the number of responders according to standard criteria in clinically assessable patients and the number of responders according to CA-125 in the CA-125 assessable patients divided by the total number of assessable patients. We have previously demonstrated how CA-125 can be used to define progression.⁶ There is now sufficient evidence to use CA-125 to define both response and progression in clinical trials.

	APPENDIX Statistical Method

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION APPENDIX Statistical Method REFERENCES

 
Each drug has an unknown efficiency, q. The probability of observing k responses out of N patients treated has a binomial distribution with parameters N and q, that is

where the right-hand side is the probability density function for B(N, q) evaluated for x = k. In the Gehan two-stage design for phase II studies, the idea is to choose a number of patients in the first stage of the trial so that the probability of observing no responses at all for a drug with a given efficacy is less than 5%. As an example, for a drug with a 20% response rate, m becomes 14. With a 10% response rate, m becomes 29.

The probability of rejection in the first stage, ie, the probability of observing zero responses in a theoretical series of m patients given that there actually were k responders among the N treated is

which can be expressed in an explicit form as

	ACKNOWLEDGMENTS

 
We thank all the trial groups that supplied data.

	NOTES

 
A.E.N. was supported by the Department of Health and by the Cancer Treatment and Research Trust.

	REFERENCES

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION APPENDIX Statistical Method REFERENCES

 
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Submitted August 17, 1999; accepted December 23, 1999.

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