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Estimating scenarios for survival time in men starting systemic therapies for castration-resistant prostate cancer: A systematic review of randomised trials

European Journal of Cancer, 11, 50, pages 1916 - 1924

Editorial comment Prof A Merseburger

This systematic review of most available published trials on mCRPC underlines the palliative setting for this disease. Often this advanced disease results in limited OS time of about 12-24 month. Those numbers shall be judged in view of the just published CHAARTED trial results of early chemotherapy in primary metastatic prostate cancer with a median OS of 3.5 years.



We sought to estimate worst-case, typical and best-case scenarios for survival in men starting systemic therapies for castration resistant prostate cancer (CRPC).


We sought randomised phase 3 trials of systemic therapies for CRPC and recorded the following percentiles (represented scenario) from Kaplan–Meier overall survival (OS) curves: 90th (worst-case), 75th (lower-typical), 50th (median), 25th (upper-typical) and 10th (best-case). We determined the accuracy of using simple multiples of the median OS to estimate the other selected percentiles from each curve: 0.25 for 90th, 0.5 for 75th, 2 for 25th and 3 for 10th. Estimates were deemed accurate if within 0.75–1.33 times the actual value.


We reviewed 23 trials (13,909 men) with 48 treatment groups including 28 of chemotherapy, and three of novel hormonal agents. In trials of first-line docetaxel, the mean (interquartile range) for median OS was 19 months (17–20), and for each scenario was: worst-case 7 months (6–8); lower-typical 12 months (11–13); upper-typical 29 months (27–31); and best-case 40 months (34–44). For trials of novel hormonal agents after chemotherapy the mean values were: median OS 17 months, worst-case 5 months, lower-typical 9 months, upper-typical 24 months and best-case not reported. Simple multiples of the median gave accurate estimates of the worst-case scenario in 72% of OS curves, lower-typical in 89%, upper-typical in 84% and best-case in 84%.


Simple multiples of the median OS from randomised trials provided accurate estimates of worst-case, typical and best-case scenarios for survival time in men starting systemic therapies for CRPC.

Keywords: Prostate cancer, Chemotherapy, Survival time, Prognosis.

1. Introduction

Castration-resistant prostate cancer (CRPC) occurs in 10–20% of those diagnosed with prostate cancer, the second most common cancer and sixth most common cause of cancer death in men [1] and [2]. Chemotherapy with docetaxel has been the standard of care for metastatic CRPC following its approval by the US FDA in May 2004, but a panoply of new treatments has subsequently become available, five of which have been shown to improve overall survival (OS) [3] . Clinicians caring for men with CRPC are currently facing the challenge of how best to explain and sequence these new therapies to maximise their net benefits.

Surveys of patients with advanced cancer have found that the majority want quantitative information about their likely survival time, including best-case and worst-case scenarios, and that prognostic information should be honest but also convey hope [4], [5], and [6]. Despite these findings, doctors rarely provide patients with quantitative estimates of survival time, talk about prognosis less than other aspects of the disease and frequently avoid the subject entirely [5] and [6]. Furthermore, when prognostic information is provided, patients frequently misunderstand it [5] and [7].

We have previously shown that selected percentiles of an OS curve can be used to estimate and explain worst-case, typical and best-case scenarios for survival time: the 90th percentile (the maximum survival time in the 10% of patients living the shortest) to reflect a worst-case scenario, the 75th to 25th percentiles (the middle 50% of survival times) to reflect a typical scenario and the 10th percentile (the minimum survival time in the 10% of patients living the longest) to reflect a best-case scenario [8] . In systematic reviews of first-line chemotherapy trials for advanced non-small cell lung cancer (NSCLC) and metastatic breast cancer (MBC), we found that simple multiples of each OS curve’s median could be used to estimate its percentiles corresponding to these scenarios for survival [9] and [10]. The worst-case scenario could be estimated as one-quarter of the median OS, the typical scenario as half to double the median OS, and the best-case scenario as three times the median. In related work, we have demonstrated that patients find survival information presented as three scenarios easier to understand, reassuring and preferable to receiving a single estimate of the median survival [11] .

The purpose of the current study was to find and summarise survival data from recent randomised trials of systemic therapy in CRPC. We also sought to determine the accuracy of using simple multiples of the median OS to estimate worst-case, typical and best-case scenarios for survival. Such information is intended to help clinicians better estimate and explain survival time in men starting such treatments for CRPC.

2. Methods

We searched MEDLINE for randomised trials of systemic therapy for CRPC. Search terms included the headings ‘prostatic neoplasms’, ‘drug therapy’, ‘antineoplastic agents’, ‘antimitotic agents’ and heading and text-word searches for the generic and brand names of pharmacological agents listed in recent reviews of prostate cancer [3], [12], and [13].

One author conducted the initial search and filtering, and two authors independently screened the references and selected trials meeting the following inclusion criteria: randomised phase 3 trial of systemic therapy for men with CRPC including at least 80 patients enrolled per treatment arm, and a Kaplan–Meier curve for OS. Trials evaluating bone directed therapies were excluded. Trials were classified as either first-line therapy (i.e. no previous cytotoxic chemotherapy) or second-line therapy (i.e. following progression after one line of cytotoxic chemotherapy).

For each eligible trial, we recorded the journal and year of publication, the definition of castration-resistance, the median follow-up time and the number of treatment arms.

For each treatment arm, we recorded the names and schedules of the drug therapies, the numbers of patients and summary of data describing the baseline characteristics of the included patients, tumours, biochemical markers and previous treatments.

Each OS curve was independently traced by two authors using UN-SCAN-IT graph digitising software [14] . The median and the following percentiles (representative scenario) were extracted from each curve: 90th (worst-case), 75th (lower-typical), 25th (upper-typical) and 10th (best-case). These percentiles are depicted in Fig. 1 . The two authors’ measurements were deemed to match if they were within 5% of each other; disagreements were resolved by repeated measurement and discussion. The measured median OS was also compared to the reported median OS to assess accuracy of measurements.


Fig. 1 Example survival curve showing percentages and their corresponding scenarios.

Based on our previous work in MBC and advanced NSCLC, we expected the OS curves to be approximately exponential, with simple multiples of each curve’s median providing reasonably accurate estimates of the selected percentiles corresponding to scenarios sought by patients [9] and [10]. We therefore hypothesised a priori that the worst-case scenario (90th percentile) would be approximately 0.25 times the median OS, the typical scenario (75th to 25th percentiles) would be approximately from 0.5 to 2 times the median OS and the best-case scenario (10th percentile) would be approximately three times the median OS. We also defined a priori that estimates would be deemed reasonably accurate if they were within 0.75–1.33 times the actual value, as in our previous studies in MBC and NSCLC.

To provide meaningful summaries of survival time based on the treatment being started, we categorised OS curves into the following clinically relevant groups:

  • (1) First-line chemotherapy with docetaxel, including trials of docetaxel in combination with investigational agents.
  • (2) Second-line chemotherapy with cabazitaxel.
  • (3) First-line therapy with a novel hormonal agent.
  • (4) Second-line therapy with a novel hormonal agent.
  • (5) Sipuleucel-T at any stage of therapy.

Factors associated with survival in trials of first-line cytotoxic chemotherapy were determined by univariable and multivariable analysis. We hypothesised that survival would be longer in treatment arms with: a more recent year of publication, docetaxel chemotherapy, a higher proportion of patients with good performance status (Eastern Cooperative Oncology Group [ECOG] 0–1), a younger median age of participants, a lower median serum prostate-specific antigen (PSA) at enrolment, a lower median serum alkaline phosphatase (ALP) at enrolment and a lower proportion of patients with visceral metastases.

3. Results

We identified 23 eligible trials including 48 randomly allocated treatment groups and 13,909 participants, published between 1993 and 2013 [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], and [37]. The reasons for exclusion are set out in Fig. 2 . Eleven trials (48%) reported a statistically significant difference in OS [16], [17], [18], [20], [21], [24], [25], [30], [31], [32], and [33], although in two of these trials the survival difference was in favour of the control arm [25] and [33].


Fig. 2 Reasons for exclusion of trials. Abbreviations: RCT, randomised controlled trial; KM, Kaplan–Meier; OS, overall survival.

The characteristics of the included trials are summarised in Table 1 . The majority of men had good performance status, bone metastases and no documented visceral metastases. The follow-up time in many trials was relatively short and insufficient to report the median OS in two treatment arms [16] and [31], the 25th percentile in 11 treatment arms, and the 10th percentile in 23 treatment arms. Values for median OS extracted from the Kaplan–Meier curves were within one month of the reported value in 100% of cases.

Table 1 Characteristics of the 23 included trials.

Characteristic Trials    
Trial characteristics No. %    
Year of publication
 2010–2013 10 43    
 2005–2009 5 21    
 2000–2004 4 18    
 1993–1999 4 18    
No. of treatment groups per trial
 2 21 91    
 3 2 9    
Journal of publication
 Journal of Clinical Oncology 10 43    
 New England Journal of Medicine 4 17    
 Cancer 3 13    
 Lancet Oncology 2 9    
 Annals of Oncology 1 4    
 British Journal of Cancer 1 4    
 Lancet 1 4    
 Urology 1 4    
Agents used in the 48 treatment groups
 Corticosteroid 28 58    
 Docetaxel 11 23    
 Anthracycline 7 15    
 Estramustine 3 6    
 Suramin 3 6    
 Vinca alkaloid 3 6    
 Abiraterone 2 4    
 Diethylstilbestrol 2 4    
 High-dose oral calcitriol 2 4    
 ET1A (atrasentan; zibotentan) 2 4    
 Sipuleucel-T 2 4    
 Bevacizumab 1 2    
 Bisphosphonate 1 2    
 Cabazitaxel 1 2    
 Enzalutamide 1 2    
 Satraplatin 1 2    
  No. reporting % Median Range
Median No. of patients per group 23 100 252 78–800
Median age, years 22 96 70 67–76
Median follow-up, months 10 43 19 12–36
ECOG performance status 0–1, % 21 91 91 58–100
Median PSA at study entry, ng/mL 21 91 106 13–209
Bone metastases, % 15 65 90 0–100
Liver metastases, % 11 48 8 0–16
Lung metastases, % 10 43 8 0–15
Median ALP at study entry (IU/L) 11 48 130 90–286
Median LDH at study entry (U/L) 7 30 202 177–238
Previous prostatectomy, % 9 39 35 8–54

Abbreviations: ET1A, endothelin-1 receptor antagonist; ECOG, Eastern Cooperative Oncology Group; PSA, prostate-specific antigen; ALP, alkaline phosphatase; IU/L, international units per litre; LDH, lactate dehydrogenase; U/L, units per litre.

For the 46 treatment arms with a reported median OS, 0.25 times the median OS accurately estimated the 90th percentile (worst-case scenario) in 72% of OS curves, 0.5 times the median OS accurately estimated the 75th percentile (lower-typical scenario) in 89% of curves, two times the median OS accurately estimated the 25th percentile (upper-typical scenario) in 84% of curves, and three times the median OS accurately estimated the 10th percentile (best-case scenario) in 84% of curves. The accuracy of using simple multiples of the median survival was independent of the duration of median survival and type of therapy used.

The 48 treatment arms included 11 with first-line docetaxel, one with a first-line novel hormonal agent (abiraterone), one with second-line cabazitaxel, two with a second-line novel hormonal agent (one abiraterone and one enzalutamide) and two with Sipuleucel-T. Table 2 summarises the survival times for each scenario in each of these groups of treatments. Median survival with abiraterone was not reported in the study of first-line novel hormonal agents [31] .

Table 2 Overall survival in each scenario and treatment group.

Treatment group (n) Average (range) in months
Worst-case Lower-typical Median OS Upper-typical Best-case
1st-line docetaxel a 11 7 (5–9) 12 (8–14) 19 (17–23) 29 (23–36) 40 (30–50)
2nd-line cabazitaxel 1 5 (5–5) 9 (9–9) 15 (15–15) 29 (29–29) NR
1st-line novel hormonal agent 1 13 (13–13) 22 (22–22) NR NR NR
2nd-line novel hormonal agent 2 5 (4–5) 9 (8–10) 17 (16–18) 24 (24–24) NR
Sipuleucel-T 2 7 (7–7) 14 (12–15) 25 (23–26) 45 (45–45) 57 (57–57)

a Including docetaxel in combination with investigational agents which did not improve prognosis.

Abbreviations: n, number of treatment groups; OS, overall survival; NR, not reported.

Distributions of the various survival times in the 25 treatment arms of first-line chemotherapy were roughly symmetrical (see Fig. 3 ).


Fig. 3 Distribution of scenarios for survival time in 25 trials of first-line cytotoxic chemotherapy.

Associations between the characteristics of the treatment arms in trials of first-line chemotherapy and the reported median OS are shown in Table 3 . The only independently significant predictors of longer median OS in a treatment arm were a lower percentage of patients with bony metastases and a more recent year of publication.

Table 3 Associations between treatment group characteristics and median overall survival in months for 25 trials of first-line chemotherapy.

Characteristic Difference in median survival (months)
Univariable linear regression Multivariable linear regression
Estimate a 95% CI p-value Estimate a 95% CI p-value
Year of publication 0.58 0.45 to 0.71 <0.001 0.57 0.21 to 0.57 <0.001
Bone metastases (%) −0.55 −0.77 to −0.33 <0.001 −0.45 −0.50 to −0.12 0.003
Docetaxel versus other 6.48 4.54 to 8.41 <0.001      
ECOG 0–2 (%) 0.28 0.18 to 0.38 <0.001      
Median age (years) −1.62 −3.13 to −0.11 0.04      
Lung metastases (%) 0.64 −0.16 to 1.44 0.1      
Median PSA (ng/mL) −0.014 −0.05 to 0.02 0.4      
Liver metastases (%) −0.43 −1.66 to 0.81 0.5      
Median ALP (IU/L) −0.003 −0.022 to 0.016 0.8      

a Number of months difference in median overall survival associated with a one-unit increase in trial characteristic.

Abbreviations: CI, confidence interval; ECOG, Eastern Cooperative Oncology Group; PSA, prostate-specific antigen; ALP, alkaline phosphatase; IU/L, international units per litre.

4. Discussion

In this study of 23 trials of systemic therapy for CRPC, we expected and found that the OS curves were approximately exponential, and that simple multiples of each curve’s median survival time generally provided accurate estimates of its other selected percentiles, corresponding to worst-case (one-quarter of the median), typical (half to double the median) and best-case (triple the median) scenarios for survival time. The average values in trials of first-line chemotherapy with docetaxel were a median OS of 19 months, with a worst-case scenario of less than 7 months, a typical scenario of 12–29 months and a best-case scenario of more than 40 months.

This study builds on our previous work in advanced NSCLC and MBC [9] and [10]. Taken together, our work supports the hypothesis that OS curves have a roughly exponential shape in trials of systemic therapy for advanced cancer. This means that simple multiples of the median OS can be used to calculate scenarios for survival time that are reasonably accurate and match the preferences of patients wanting information about their survival prospects. The results from this study in CRPC support the extension of our method for estimating scenarios for survival beyond patients starting first-line chemotherapy to patients starting endocrine therapy, immune therapy and second-line chemotherapy.

We considered the multiples of the median reasonably accurate for estimating scenarios when the estimates were within 0.75–1.33 times the actual values. This criterion is arbitrary but was specified a priori and consistent with our previous work on cytotoxic chemotherapy for advanced NSCLC and MBC [9] and [10]. Using this criterion, the accuracy of our method for estimating the worst-case scenario was 72%, which is similar to our previous work with MBC (73%) and advanced NSCLC (78%). In all three studies there was a systematic tendency for one-quarter of the median OS to under-estimate the survival in the 5–10% of patients doing worst; this is probably explained by the exclusion from trials of patients with an obviously poor prognosis and a life expectancy less than 3 months. Conversely, the multiples method tended to overestimate survival in the upper-typical and best-case scenarios. This apparent tendency to overestimate best-case survival times is probably due to the follow-up in many reports being too short to reliably estimate the proportions of patients with these longer survival times.

This study has important clinical implications. When patients with CRPC seek quantitative information on survival we suggest doctors start with an estimate of the median survival in a group of similar patients. The median OS from a recent clinical trial provides a good starting point, and will be most accurate if the trial is recent and includes similar patients receiving the intended treatment. The doctor may adjust this estimated median OS based on important prognostic factors, for example the extent of disease, performance status and comorbidities. Simple multiples of the estimated median can then be used to calculate and explain three scenarios for survival time.

For example, for a patient starting first-line chemotherapy with docetaxel and characteristics typical of patients included in the pertinent randomised trials, an estimated median survival of approximately 20 months would be a reasonable starting point and result in a calculated worst-case scenario of 5 months or less (0.25 of 20), a typical scenario of 10–40 months (0.5–2 times 20), and a best-case scenario of more than 60 months (three times 20). These scenarios could be explained using words like: ‘if we imagine 100 people in exactly the same situation then we’d expect the 5 to 10 who did worst to die within 5 months, the middle 50 to live between 10 and 40 months, and the 5 to 10 who did best to live longer than 5 years.

Most patients with advanced cancer want information about their prognosis, and at least half expect their clinician to initiate this discussion [6] and [38]. Such a discussion should therefore be tactfully proffered at some point to all patients. To maximise the availability and accuracy of scenario-based data, for which patients have a preference [11] , we propose that future randomised trials of drug therapy in advanced cancer report the worst-case, best-case and typical scenarios for survival as defined in this paper, and that they follow patients longer to obtain more accurate best-case scenario data.

Good communication of prognosis to patients is associated with lower scores for depression and anxiety, and higher scores for patient satisfaction [5] . When communicating prognosis to patients, clinicians can struggle to provide realistic survival data without removing a patient’s sense of hope. Many patients may desire honesty while simultaneously preferring some ambiguity to allow them to hope for a possible better outcome [6] . Our method offers a way of resolving these tensions by providing honest, accurate estimates for a range of scenarios that allow patients to hope for a realistic best-case scenario, while at the same time prepare for realistic typical and worst-case scenarios.

Many oncologists are reluctant to give specific estimates of prognosis, for fear of being wrong, of distressing patients and of suffering legal consequences for inaccurate estimation [5] and [6]. Our method of communicating survival time as three scenarios helps overcome these barriers. The variability and uncertainty of survival time are conveyed more accurately by giving scenarios couched as ranges than by giving a single point estimate of median survival that conveys unwarranted precision.

Our study has several strengths. This is the most comprehensive summary of survival data in men with CRPC treated with contemporary systemic therapies. Kirby and colleagues noted the heterogeneity of definitions of CRPC and the difficulty of determining survival based on epidemiological data [2] . Furthermore, our work covers the full suite of modern treatments for CRPC that have been validated in phase III randomised controlled trials, including hormonal, chemotherapeutic and immunologic treatments. The consistent accuracy of our findings across these modalities, and across other cancers, supports the broader applicability of our methods.

The main limitation of this review is that it includes only patients in clinical trials, who have a better prognosis than patients treated similarly in routine clinical practice. There are few data available on the survival in patients outside clinical trials, so we propose clinicians start with the estimates from trials and adjust these estimates up or down to reflect the differences between a routine practice patient and the typical trial patient. A further limitation is that the reported follow-up times for the newest treatments are relatively short, particularly in the trial of first-line abiraterone [31] . This means that the values for the upper limit of the typical scenario and the best-case scenario are less reliable than those for the shorter survival times.

Our study was not designed to estimate the effects of specific treatments on survival: this would require formal meta-analysis of randomised trials directly assessing comparable treatments. The observed variations in survival times between the different treatment groups are a composite effect of the patients’ differing baseline characteristics and of the various treatments being compared. Our study was not designed to determine the effects of individual prognostic factors; this would require analysis of individual patient data. However, consistent with studies of prognosis based on individual patient data [39], [40], and [41], we found that increased survival time was associated with an absence of bone metastases (less extensive disease), and a better performance status. In contrast to other studies, we did not demonstrate associations between longer survival and lower ALP or absence of liver metastases [39], [40], and [41], probably a reflection of varying entry criteria and inconsistent reporting of these factors in our included trials.

OS distributions in trials of systemic therapy for CRPC were remarkably similar in shape with median survival times differing according to the characteristics of the patients and their treatments. For most of the 48 OS curves from the 23 trials included in this study, multiples of each curve’s median gave reasonably accurate estimates of its other selected percentiles corresponding to worst-case (0.25 times the median), typical (0.5–2 times the median) and best-case (three times the median) scenarios for survival. Presenting these scenarios to men with CRPC starting these treatments should provide prognostic information that is realistic, understandable, honest and leaves room for hope.


TW conducted the literature review, paper identification and figure production. TW and BK jointly performed data extraction, interpretation and analysis and wrote the manuscript. MS designed the study and provided oversight and guidance on all of its aspects.

Role of funding source

The sponsor of the study had no role in study design, data collection, data analysis, data interpretation or writing of the report.

All authors had full access to study data, have read the paper and agree with its content. The corresponding author had responsibility for the decision to submit for publication.

Conflict of interest statement

None declared.


Supported by grants from the Australian National Health and Medical Research Council.


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a Sydney Medical School, University of Sydney, Edward Ford Building A27, NSW 2006, Australia

b National Health and Medical Research Council Clinical Trials Centre, University of Sydney, Locked Bag 77, Camperdown, NSW 1450, Australia

c Department of Medical Oncology, Sydney Cancer Centre, RPA and Concord Hospitals, Missenden Road, Camperdown, NSW 2050, Australia

lowast Corresponding author at: NHMRC Clinical Trials Centre, Locked Bag 77, Camperdown, NSW 1450, Australia. Tel.: +61 2 9562 5313; fax: +61 2 9565 1863.

Presented in part at the Australian and New Zealand Urogenital and Prostate (ANZUP) Cancer Trials Group Annual Scientific Meeting, Gold Coast, Australia, 2013.