The second remission population is ideal to evaluate consolidation strategies since nearly all patients will have disease progression over a short time period of 9–15 months. (7) The different disease states in recurrent ovarian cancer patients who are receiving consolidation therapy after second remission have been described previously. (10) Historical estimates of PFS for this population from phase II consolidation trials often include variable duration of second-line therapy (SLT), possibly a treatment free interval (TFI) and the time on investigational therapy (IT). For example, common practice does not distinguish a consolidation strategy that consists of 10 months on SLT followed by 3 months on IT, versus a strategy that consists of 3 months on SLT followed by 10 months on IT. If both strategies have a median PFS of 13 months, does either strategy warrant a phase III trial? Was the investigational therapy received long enough to allow effect?

Furthermore, the patient populations across phase II consolidation trials in second line non-randomized setting have not been selected in a consistent way in terms of previous line of treatments, and whether they are enrolled and start IT along with SLT at the time of primary recurrence or after they have achieved complete response. Furthermore, some trials enroll patients in strict second CR or greater, while other trials enroll patients who have achieved a partial response (PR) or stable disease (SD). The heterogeneity in patient population and lack of randomization in single arm studies make it difficult to compare consolidation regimens on the basis of PFS since the results of one strategy might not be generalizable to another study. The key question is how to decide if a single-arm consolidation trial shows enough promise to move forward to a randomized Phase III trial.

We calculated the sample sizes required to have 80% power in order to show an increase in estimated median PFS from 9 to 13.5 months, which corresponds to a 33% hazard reduction, using two different starting points for PFS definition. We partitioned PFS in three intervals by expressing it as the sum of the duration of SLT, TFI and IT (i.e., PFS=SLT+TFI+IT, Figure 1) and calculated the sample size under different values of SLT, TFI and starting point of IT. We assumed that PFS follows exponential distribution from the start of SLT with a drop in hazard at the start of IT, that the magnitude of the drop does not depend on starting time, and that patients are followed until failure. All tests are one-sided, single arm comparisons at P ≤0.05. Details regarding the calculations can be found in the appendix.

We evaluated two endpoints: PFS from SLT was defined as the time from the start of SLT to disease progression or death (the traditional definition); PFS from IT was defined as the time from the start of IT to disease progression or death. Power calculations used intent-to-treat paradigm by including all eligible patients at the start of SLT for the first endpoint. However, for the calculation of PFS from IT, patients must be in clinical remission at the time of IT, i.e., patients who progress prior to initiation of IT are excluded. The assumptions for the respective designs using the above endpoints are summarized in Table 1. We also evaluated power and sample size requirements for three treatment strategies, as shown in Figure 2. Consider the start and end dates of second-line therapy (SLT) as points A and B respectively, and the start of protocol/investigational therapy as point C.

Table 2 shows sample sizes required to achieve 80% power, and a 33% hazard improvement from a historical estimate of PFS of 9 months at varying starting points for IT. For example, a study of 34 patients will provide 80% power only if the IT starts concurrently with SLT, after recurrence from primary treatment. If IT starts 4.5 months after SLT, which corresponds to 6 cycles of chemotherapy every 3 weeks, then 67 patients are required for a single-arm trial. If IT starts after completing 6 months on SLT, 84 patients are required. If one accrues only 34 patients at start of SLT with planned 33% hazard reduction and the duration of SLT delays the start of IT to 7.5 months, the power drops to 50% (Figure 1. Supplemental Material). To maintain 80% power in this scenario, either the IT would have to reduce the hazard by 50%, or the sample size would have to increase to approximately 104 events. Note that only 81 out of 104 patients will receive IT, since some patients would progress before 7.5 months. This calculation uses the traditional definition of PFS (i.e., start of chemotherapy to progression). The advantage of this design is that the results are generalizable to the patient population observed right after first progression, and historical estimates of PFS are available since this design uses the traditional definition of PFS. However, all patients must be followed up from initiation of SLT, although a smaller number of patients will respond and receive the IT, hence longer follow-up and more resources are required.

Using Design 2 and the respective endpoint, the starting point of PFS is the start of IT, regardless when IT starts. Assuming the effect size is 33% in hazard reduction and seeking 80% power, the sample size needed at the start of the IT is 34 patients. The later the investigational therapy begins, the more patients need to be screened since patients might become ineligible due to progression prior to initiation of IT (Table 3). For example, if IT starts 7.5 months after the start of SLT, then we expect 10 ineligible patients due to progression before 7.5 months; thus, 44 patients need to be screened in order to enroll 34 eligible patients at 7.5 months.

It is acknowledged that the question of whether IT is efficacious can be best answered in a Phase III definitive trial of comparing two randomized arms, namely SLT alone and SLT with consolidation therapy added, ie SLT+IT. If power is reduced, randomized Phase II trials would also provide a head to head comparison with a concurrent control and the lack of historical estimates would be eliminated (14). However, in order to design randomized studies we need meaningful PFS estimates for the control arm and the expected improvement in which to base the sample size required. These estimates are always based on smaller Phase II trials. Furthermore, when a larger randomized Phase II trial is not feasible, single-arm consolidation trials remain a viable option in identifying agents with activity before committing to move into a larger confirmatory trial.

Our focus has been second line therapy, but the question of what is considered a clinically meaningful improvement and when PFS should start applies to consolidation trials in other lines of treatments. In primary therapies these issues are less critical because the duration of first line therapy is typically uniform, averaging from 6–8 cycles whereas the duration of second line therapy can be more variable. For example the Phase III trial known as SWOG S9761/GOG 178 (15) in which advanced stage OC patients with complete response to platinum/taxane therapy were randomized to receive either 3 or 12 cycles of monthly paclitaxel showed a significant improvement in PFS favoring 12 cycles (median PFS 22 vs 14 months; pvalue=0.006) when PFS was measured from the start of first line therapy and front line therapy was restricted to 5–6 cycles. On the other hand, the Oregovomab trial (16) which randomized advanced OC patients to maintenance immunotherapy or placebo after 4 to 12 weeks of front line therapy showed no improvement with median PFS of 10.3 (oregovomab) vs 12.9 (placebo) pvalue=0.2, when PFS was measured from randomization 4 to 12 weeks after the end of front line therapy. The estimate from GOG 178 includes the time of front line therapy, while it correctly restricts it per protocol, while the Oregovomab trial excludes the time of front line therapy by starting PFS at randomization and allowing a TFI of 4 to 12 weeks prior to randomization. While different approaches of reporting PFS are used here, the results may be compared because the duration of primary therapy is relatively consistent. However, in non randomized consolidation trials in the setting of second line treatment, the starting point of PFS is not uniformly defined and duration of SLT is not restricted and can be variable. This limits the ability to compare different studies.

In order to minimize this variability, we propose eligibility restrictions for non-randomized trials evaluating agents in the consolidation, second line setting. One approach would be to restrict the time on SLT and the TFI. The duration of SLT cannot be absolutely restricted as patients may achieve CR at variable time points, but we suggest a design allowing 5–6 cycles of SLT. In addition, if starting IT after SLT, the TFI should be similarly restricted and allow a TFI of up to 2 months from the completion of SLT to the start of IT. If these restrictions are not feasible, another approach would be to exclude SLT from the definition of PFS by calculating PFS from the start of IT, and we have shown that the benefits in terms of sample size and resources are clear in this setting. However, comparisons with historical data must be cautious. When PFS is calculated from the start of SLT, the estimates are valid for all patients enrolled after primary recurrence. When the duration of SLT is excluded from PFS definition, the estimates are less prone to bias since they measure the efficacy of the investigational treatment alone, but these estimates are valid only to patients who have achieved CR after completion of SLT and the literature is less robust in this regard.

Our study addresses the effect of the duration of SLT on the final PFS estimates under specific assumptions. Our sample size and power calculations considered a specific difference in median PFS based on our experience and the estimates reported in the literature. We assumed PFS follows exponential distribution and the hazard is constant within each treatment interval. While this assumption may not be justified when analyzing real data, it has appeal for sample size calculations due to its interpretability and simplicity and it is typically used (17). Power estimates may differ under other distributions, and such evaluation is beyond the scope of this paper. However, our conclusions about the importance of defining the starting times for IT and PFS apply in general.

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