Author response: An open label randomized controlled trial of tamoxifen combined with amphotericin B and fluconazole for cryptococcal meningitis

Article Figures and data Abstract Introduction Materials and methods Results Discussion Appendix 1 Data availability References Decision letter Author response Article and author information Metrics Abstract Background: Cryptococcal meningitis has high mortality. Flucytosine is a key treatment but is expensive and rarely available. The anticancer agent tamoxifen has synergistic anti-cryptococcal activity with amphotericin in vitro. It is off-patent, cheap, and widely available. We performed a trial to determine its therapeutic potential. Methods: Open label randomized controlled trial. Participants received standard care – amphotericin combined with fluconazole for the first 2 weeks – or standard care plus tamoxifen 300 mg/day. The primary end point was Early Fungicidal Activity (EFA) – the rate of yeast clearance from cerebrospinal fluid (CSF). Trial registration https://clinicaltrials.gov/ct2/show/NCT03112031. Results: Fifty patients were enrolled (median age 34 years, 35 male). Tamoxifen had no effect on EFA (−0.48log10 colony-forming units/mL/CSF control arm versus −0.49 tamoxifen arm, difference −0.005log10CFU/ml/day, 95% CI: −0.16, 0.15, p=0.95). Tamoxifen caused QTc prolongation. Conclusions: High-dose tamoxifen does not increase the clearance rate of Cryptococcus from CSF. Novel, affordable therapies are needed. Funding: The trial was funded through the Wellcome Trust Asia Programme Vietnam Core Grant 106680 and a Wellcome Trust Intermediate Fellowship to JND grant number WT097147MA. Introduction Cryptococcal meningitis is a leading cause of death in HIV-infected patients, with an estimated 223,000 cases in 2014 (Rajasingham et al., 2017). The vast majority of infections are due to C. neoformans, and occur in low-income tropical settings. Current international guidelines recommend initial induction treatment with amphotericin combined with flucytosine, followed by consolidation therapy with fluconazole (World Health Organization, 2018). This combination delivers the fastest rates of clearance of yeast from cerebrospinal fluid (CSF) and the best survival rates (Day et al., 2013; Molloy et al., 2018). However, even on this gold standard therapy, 30% of patients will die within 10 weeks of diagnosis (Day et al., 2013; Molloy et al., 2018). Adjunctive therapy with corticosteroids, which has proven beneficial in other forms of meningitis, results in worse outcomes (Beardsley et al., 2016). Cryptococcal meningitis can also occur in HIV-uninfected patients, including immunocompetent people and those with other causes of immunosuppression. Survival rates are similar to those seen in HIV-infected patients. There are few data from randomized controlled trials to guide treatment in these circumstances. In Vietnam around 20% of cases of cryptococcal meningitis are in HIV-uninfected patients (Chau et al., 2010). Disease is predominantly due to the C. neoformans VNIa-5 lineage; C. gattii is responsible for around 25% of cases (Chau et al., 2010; Ashton et al., 2019; Day et al., 2011; Day et al., 2017). There has been little progress in development of antifungal drugs for cryptococcal meningitis. Amphotericin and flucytosine are each more than 60 years old; the last novel drug class developed was the azoles, introduced 30 years ago. Access to flucytosine is severely restricted by availability and cost, meaning it is rarely used where disease burden is highest. Despite being off-patent, it has been subject to extraordinary price rises in recent years, with a 2-week course now costs around 30,000 USD in the USA (Merry and Boulware, 2016). Flucytosine is an unattractive prospect for generic manufacturers, because the location of the majority of patients and the few indications outside cryptococcal disease promise only limited financial returns. These same factors hamper the development of novel treatments for cryptococcal disease, and have driven interest in drug re-purposing (Butts et al., 2014; Dolan et al., 2009; Zhai et al., 2012). Re-purposing can be a solution for neglected diseases provided the new indication accounts for only a minority of total prescriptions, and the de facto indications are sufficiently prevalent to ensure availability, price stability, and affordability. Tamoxifen, a selective estrogen receptor modulator used to treat breast cancer, has anti-cryptococcal activity, appearing to act synergistically when combined with other antifungals against the type strain in vitro, and to be fungicidal when combined with fluconazole in the mouse infection model (Butts et al., 2014; Dolan et al., 2009). We found it to act synergistically with amphotericin against two-thirds of clinical isolates of Cryptococcus neoformans and C. gattii from our archive and to have an additive interaction when combined with fluconazole in vitro (Hai et al., 2019). Tamoxifen is concentrated in brain tissue (10- to 100-fold compared with plasma) and macrophage phagosomes (a site of growth for Cryptococcus spp.), is off-patent, cheap (~10US cents/tablet) and widely available (Lien et al., 1991a; Lien et al., 1991b). Therefore, it is a promising candidate for the treatment of cryptococcal meningitis. Pharmacokinetic data suggest that doses 5- to 10-fold that used in breast cancer (typically 30 mg/day) should deliver plasma concentrations of tamoxifen greater than the Minimum Inhibitory Concentration 90 (MIC90 16 µg/mL) of Vietnamese clinical isolates (Lien et al., 1991a). Such doses have been used, and well-tolerated, in small cell lung cancer, desmoid tumours, and prostate cancer. These illnesses have comparable or better 1-year survival rates than cryptococcal meningitis (Ngan et al., 2019). While generally well-tolerated, acute side effects that could be detrimental from short-course treatment include QT prolongation of the cardiac de/repolarization cycle, although the risk of life-threatening arrhythmias appears to be low (Grouthier et al., 2018). In Vietnam induction treatment for cryptococcal meningitis consists of amphotericin combined with fluconazole, consistent with WHO recommendations where flucytosine is unavailable (World Health Organization, 2018). However, this combination is less effective than amphotericin with flucytosine, resulting in slower rates of fungal clearance and worse survival rates (Day et al., 2013; Molloy et al., 2018). The relationship between the rate of fungal clearance from CSF and survival is generally robust; improving the potency of antifungal therapy is likely to be an effective way to reduce deaths (Day et al., 2013; Molloy et al., 2018; Beardsley et al., 2016). The rate of clearance of yeast from CSF associated with an antifungal treatment (the early fungicidal activity, EFA) is a sensitive measure able to detect differences between treatment regimens likely to be associated with survival benefits with far fewer patients than studies powered to survival itself (Brouwer et al., 2004). Small studies powered to this endpoint can serve to filter treatment regimens that can be taken forward in larger trials (Brouwer et al., 2004; Bicanic et al., 2009). We performed an open-label randomised controlled trial to determine whether combining tamoxifen with amphotericin B and fluconazole results in enhanced EFA in HIV infected and uninfected patients with cryptococcal meningitis, and to generate safety data as a prelude to a larger trial powered to mortality (Ngan et al., 2019). Materials and methods Study design and participants Request a detailed protocol The study design is described in detail in the published protocol (Ngan et al., 2019). In brief, we enrolled 50 patients in two hospitals in Ho Chi Minh City – the Hospital for Tropical Diseases and Cho Ray Hospital. Eligible adult patients (≥18 years of age) had a clinical syndrome consistent with cryptococcal meningitis and one or more of: (1) positive cerebrospinal fluid (CSF) India ink; (2) C. neoformans cultured from CSF or blood; (3) positive cryptococcal antigen Lateral Flow Antigen Test (LFA) in CSF. All patients were tested for HIV infection in accordance with standard of care. We excluded patients who were pregnant, had a history of thromboembolic disease, had received more than 4 days of anti-cryptococcal antifungal therapy, had any other indication for tamoxifen, had renal failure, or a rate-corrected (Framingham formula) QT interval >500ms. Written informed consent was obtained from all patients or their representatives. Interventions Request a detailed protocol Patients were randomized to receive either standard of care induction antifungal therapy or standard of care plus tamoxifen. Standard of care antifungal therapy consisted of intravenous amphotericin B deoxycholate 1 mg/kg/day (Amphotret, Bharat Serums and Vaccines, India) combined with oral fluconazole 800 mg/day (Zolmed, Glomed Pharmaceuticals, Vietnam) for the first 14 days following randomization. Tamoxifen (Nolvadex, AstraZeneca UK Ltd) 300 mg/day was given orally. Amphotericin was infused over 4 hr after prehydration with normal saline and potassium supplementation (Khoo et al., 1994). Fluconazole and tamoxifen were administered simultaneously. All medication was directly observed while the patient was in hospital; all participants were in-patients for at least the first 14 days of the study. Following induction therapy all patients received fluconazole 800 mg once daily for 8 weeks. HIV-infected patients received daily pneumocystis prophylaxis with trimethoprim– sulfamethoxazole. Antiretroviral therapy was instituted 5–6 weeks after diagnosis via the national treatment programme. Randomization Request a detailed protocol Randomization was in a ratio of 1:1, in blocks of 4 or 6, stratified by HIV serostatus (rapid test) and treating centre. The computer generated randomization list was password protected and stored on a secure server to which only the study pharmacist had access. Enrolment logs specific to each centre were used to assign patients to the next available sequential number and corresponding sealed treatment pack. Outcome measures Request a detailed protocol The primary outcome was Early Fungicidal Activity (EFA), defined as the rate of decline in culturable yeast from CSF over the first 2 weeks following randomization. Secondary outcomes included survival until 10 weeks after randomization, disability at 10 weeks, frequency of grade 3, 4 or serious adverse events, immune reconstitution inflammatory syndrome (IRIS), QTc prolongation, visual deficit at 10 weeks, and time to new neurological events. Adverse events were defined according to the Common Terminology Criteria for Adverse Events (CTCAE) and categorized according to the Medical Dictionary for Regulary Activities system organ class. We categorized prolonged QTc intervals using this classification as normal (<450 ms for males, <460 ms for females), mildly prolonged (grade 1 or 2, ≥450 ms for males or ≥460 for females but ≤500 ms) and grade 3 or 4 (>500ms). Disability at 10 weeks was categorised as good, intermediate, poor, or death, as described previously (Day et al., 2013; Beardsley et al., 2016). Monitoring and laboratory investigations Request a detailed protocol Lumbar puncture was performed on study entry, days 3, 7, and 14 following randomization, and more frequently if indicated. Fungal burden was determined as previously described (Day et al., 2013). Twelve-lead electrocardiograms were recorded twice daily (10 s at 50 mm/sec), immediately before and 2 hr after administration of tamoxifen during the first 14 days, and on days 21 and 28. The QT interval was manually determined by measuring the interval in three limb and three chest leads, to calculate the median. The median QT interval was corrected (QTc) for rate using the Framingham formula[20]. Calmodulin inhibitors such as tamoxifen have previously been suggested to inhibit CD4 cell apoptosis in HIV-infected patients (Pan et al., 1998). CD4 counts were measured at baseline and at study week 10. The full laboratory investigation schedule is detailed in the published protocol (Ngan et al., 2019). Outpatient assessments with medication review were performed weekly until 4 weeks and at the completion of 6 and 10 weeks; more frequent review occurred if clinically indicated. Adherence following hospital discharge was assessed using pill counts. Cryptococcus isolates were typed using URA5-RFLP and underwent (microbroth) antifungal susceptibility testing as per CLSI guidelines (CLSI, 2002; Franzot et al., 1997). Previously tested clinical isolates were included as controls. Sample size Request a detailed protocol Sample size considerations were based on two separate simulation experiments using data from our previously published trials in cryptococcal meningitis (Day et al., 2013; Beardsley et al., 2016). The estimated power was based upon 10,000 repetitions of each experiment. The full methodology is available within the published protocol (Ngan et al., 2019). Based on these simulations, enrolling 25 subjects per treatment group provided 80% and 90% power to detect a difference in EFA of −0.11 or −0.13 log10 colony-forming units/ml/day, respectively. This size of effect has previously been associated with survival benefit (Day et al., 2013; Beardsley et al., 2016). Statistical analysis Request a detailed protocol For the primary outcome, all recorded longitudinal quantitative fungal count measurements up to day 17 following randomization (allowing for some delays in the day 14 sampling) were included in the analysis. EFA, defined as the decline in fungal count (slope), was modeled based on a joint model consisting of a survival model and a linear mixed effects model with longitudinal log10 CSF quantitative culture fungal counts as the outcome. In the linear mixed effect model, we modeled the treatment groups and the time since enrolment and their interaction as fixed covariates. We used random patient-specific intercepts and slopes. The model was implemented in a Bayesian framework using Rstan. It allows appropriate handling of detection limits with longitudinal measurements and also allows adjustment for informative dropout due to early death within the first 17 days following randomization (Stan Development Team, 2019; R Development Core Team, 2018). For the secondary outcomes, overall survival was visualized using Kaplan-Meier curves for each treatment arm and the comparison between them was based on the Kaplan Meier estimates of 10-week mortality. The percentage of individuals with disabilities at 10 weeks and with adverse events of grade 3 or 4 were compared using the chi-squared test; if the expected value of any cell was less than one then Fisher’s exact test was used (Campbell, 2007). We presented the median (IQR) of the difference in CD4 counts over 10 weeks and compared their distributions using the Mann-Whitney-Wilcoxon rank sum test. We compared the trend in QTc over the period of study drug administration (i.e. the first 14 days) between the two treatment arms using a linear mixed effect model which allowed for different non-linear trends between the pre-dose and post-dose measurements. We then used the output of the fitted linear mixed effect model to compute the differences in QTc between treatment arms by study day, separately for pre-dose and 2 hr post-dose measurements. Further details of the analytical approach are available in the the Supplementary Appendix in the Statistical Analysis Plan. Results Trial recruitment The study recruited between October 2017 and May 2018. We screened 70 patients, enrolling 50 (40 HIV infected; 10 HIV uninfected) with 24 assigned to the intervention arm and 26 assigned to the control arm. Reasons for exclusion are shown in the study flow diagram (see Figure 1). One patient who was assigned to the intervention arm did not receive tamoxifen because of severe transaminitis. Figure 1 Download asset Open asset Trial flow chart: enrollment, randomization, and follow-up. Baseline characteristics The baseline characteristics of the patients were broadly balanced between treatment groups. There were slightly more patients with normal Glasgow coma scores in the control group than in the intervention group (24 of 26 versus 19 of 24, see Table 1). Table 1 Clinical and investigation characteristics of patients at study entry. CharacteristicTotalTamoxifenTotalControlNN (%) or IQR*NN (%) or IQR*Male sex2417 (71)2618 (69)Median age in years2435 (31, 39)2632 (25, 35)History of intravenous drug use243 (13)263/26 (12)HIV infection2419 (83)2621/26 (81)Current antiretroviral-therapy useNone2418 (75)2622 (84)≤3 months duration244 (17)262 (8)>3 months duration242 (8)262 (8)Median duration of illness — days2414 (10, 25)2612 (7, 28)SymptomsHeadache2424 (100)2626 (100)Fever2422 (92)2623 (88)Neck stiffness2220 (91)2621 (81)Seizures242 (8)263 (12)Abnormal visual acuity226 (27)264 (15)Papilledema212 (10)251 (4)Glasgow Coma Scale score24261519 (79)24 (92)11–145 (21)2 (8)<110 (0)0 (0)Cranial nerve palsyNone2419 (79)2623 (88)Cranial nerve VI244 (17)261 (4)Other cranial nerve241 (4)263 (11)InvestigationsMedian CSF opening pressure — cm of CSF1926.5 (18, 37)2324.5 (16, 47)Median CSF white-cell count in HIV infected patients — cells/mm31838.5 (7, 52)2027 (10, 55)Median CSF white-cell count in HIV uninfected patients — cells/mm35122 (64, 187)594 (45, 117)Median CSF glucose — mmol/l242.47 (1.70, 3.14)252.31 (1.44, 2.76)Median blood glucose — mmol/l245.86 (4.92, 6.84)266.21 (5.11, 7.81)Median CSF: blood glucose ratio240.40 (0.24, 0.53)250.37 (0.16, 0.45)Median CSF fungal count — log10 CFU/ml244.60 (3.90, 5.17)265.16 (3.17, 5.87)Median CD4 count in HIV infected patients — cells/mm31720 (8, 49)2117 (9, 45)Median CD4 count in HIV uninfected patients — cells/mm35376 (348, 382)5504 (305, 968)Median creatinine — mg/dl240.82 (0.66, 1.05)260.78 (0.66, 0.98)QTc interval — ms24395.03 (377.55, 410.45)26401.20 (374.76, 420.06) * Median, interquartile range (IQR) for continuous data and N (%) for categorical data. Primary outcome There was no detectable difference in the early fungicidal activity (EFA) of the two treatment regimens (see Figure 2A). In the intention-to-treat analysis, the rates of fungal decline per day were −0.48 and −0.49 log10colony-forming units (CFU)/ml/day in the control and tamoxifen groups respectively (difference −0.005 log10 CFU/ml/day, 95% CI: −0.16, 0.15); p-value = 0.95, (see Table 2). There was no detectable difference in EFA in the per-protocol population analysis, or by HIV infection status (see Table 2). Figure 2 Download asset Open asset The impact of addition of tamoxifen to standard treatment on (A) the rate of sterilzation of cerebrospinal fluid, and (B) survival until 10 weeks after randomisation. (A) Decline in fungal count in CSF as measured in colony-forming units (CFU) per milliliter over the first 2 weeks of treatment by treatment arm. Data from individual patients are shown in grey lines. Bold blue lines show estimated mean with 95% credible intervals (shaded band) of CSF fungal counts based on the joint model described in the statistical analysis. The rate of decline was −0.49 log10CFU/ml/day in patients receiving tamoxifen versus −0.48 log10CFU/ml/day in control patients. The horizontal dashed lines represent the value of detection limit (4.5 CFU/ml). The fitted line crosses the horizontal dashed lines of the detection limit value after day 8 because 25% and 75% of patients had fungal counts under the detection limit at days 8 and 15, respectively. (B) Kaplan-Meier survival cures for each study arm over the 10-week study period. Seven death events occurred in the control arm versus 8 in the tamoxifen intervention arm by 10 weeks (estimated risk 27% versus 34%, absolute risk difference = 6.5%) (95% Confidence Interval −19.2 to 32.1%, p = 0.62). Table 2 Primary outcome: Early Fungicidal Activity over the first 2 weeks following randomization (log10 colony-forming units (CFU)/ml/day). Treatment ArmAnalysis populationsTotalTamoxifenTotalStandard of CareDifference in changep-value†NChange/day (95% CI*)NChange/day (95% CI*)(95% CI*)Intention-to-treat24−0.49 (−0.62,–0.37)26−0.48 (−0.61,–0.37)−0.005 (−0.16, 0.15)0.95Per-protocol23−0.48 (−0.61,–0.36)25−0.48 (−0.61,–0.37)0.004 (−0.17, 0.17)0.96HIV-infected patients19−0.49 (−0.65,–0.37)21−0.42 (−0.55,–0.31)−0.072 (−0.25, 0.10)0.41HIV-uninfected patients5−0.42 (−0.74,–0.21)5−0.57 (−0.93,–0.33)0.16 (−0.18, 0.55)0.37 *95% CI corresponds to Bayesian 95% credible intervals. †p-value refers to crude ‘Wald-type’ tests of the mean estimate divided by its standard deviation of the Monte Carlo Markov chain sampling of coefficients derived from the joint model. Secondary endpoints The secondary outcomes in terms of mortality, disabilities, and change in CD4 count are summarized in Table 3. Death occured in 8 of 24 patients in the tamoxifen group and 7 of 26 in the control group (Kaplan-Meier mortality estimates 34% and 27% respectively, risk difference 6.5%; 95% confidence interval [CI], −19.2 to 32.1%; P=0.62 Figure 2B). Fewer patients in the tamoxifen arm were classified as having a good outcome at 10 weeks compared with the control arm (9% versus 36%). We found no difference in change in CD4 counts in HIV patients by study arm over the 10-week period of follow-up (see Table 3). Table 3 Secondary outcomes: death, disability, and change in CD4 count. Death by 10 weeksTamoxifen N/total (%)Control N/total (%)Risk difference % (95% CI)p- value*Intention-to-treat population8/24 (34)7/26 (27)6.47 (−19.15, 32.09)0.62Per-protocol population7/23 (31)6/25 (24)6.50 (−18.90, 31.89)0.62HIV infected patients7/19 (37)6/21 (29)8.39 (−20.99, 37.77)0.58HIV uninfected patients1/5 (20)1/5 (20)0.00 (−49.58, 49.58)1.00Disability at 10 weeks0.14Good2/23 (9)9/25 (36)Intermediate7/23 (30)6/25 (24)Severe disability6/23 (26)3/25 (12)Death8/23 (35)7/25 (28)Disability at 10 weeks in HIV infected patients0.05Good2/18 (11)8/20 (40)Intermediate5/18 (28)6/20 (30)Severe disability4/18 (22)0/20 (0)Death7/18 (39)6/20 (30)Disability at 10 weeks in HIV uninfected patients0.68Good0/5 (0)1/5 (20)Intermediate2/5 (40)0/5 (0)Severe disability2/5 (40)3/5 (60)Death1/5 (20)1/5 (20)Change in CD4 count over 10 weeks (cells/uL)Median Change (IQR) (N)Median Change (IQR) (N)HIV-infected patients50.0 (5.00, 142.5) (10)40.0 (7.0, 76.0) (13)0.5HIV-uninfected patients393.5 (211.3, 613.8) (4)−257.5 (−413.7,–171.0) (4)0.02 *p-Values not corrected for multiple testing. The number of patients having grade 3 or 4 adverse events were similar between treatment arms (see Table 4), with the exception of QTc prolongation events. Eight patients had grade 3 or 4 QTc prolongation events in the tamoxifen arm, compared with one in the control arm (p=0.02). The trend and difference in QTc intervals over the first 2 weeks of treatment are shown in Figure 3. Tamoxifen resulted in QTc prolongation over the 2-week treatment period (p<0.001). Figure 3 Download asset Open asset Change in QTc interval over the first 2 weeks of treatment by study arm. Faint lines display change in individual patient QTcs; bold lines display the estimated mean and shaded bands the 95% Confidence Intervals; blue = control arm, red = tamoxifen arm. The maximum median difference in the QTc intervals between study arms immediately prior to drug administration was 37.07 ms (95% CI: 21.09, 53.04) and occurred on day 9 of the study. The largest difference in median QTc 2 hr post-drug administration was 33.44 ms (95% CI: 18.67, 48.21) and occurred on day 8 of the study. Additional details regarding change in QTc are provided in the Supplementary Appendix. Table 4 Grade 3 or 4 adverse events by 10 weeks. EventTamoxifen (N = 24)Control (N = 26)p-value*Number of patients with Grade 3 or 4 adverse events (%)Any adverse event24 (100)26 (100)1.0New neurological events9 (38)7 (27)0.62New AIDS-defining illness (HIV patients only)3 (16)5 (24)0.58New cardiac events9 (38)4 (15)0.145Supraventricular tachycardia1 (4)0 (0)0.48Ventricular extrasystoles3 (13)0 (0)0.21Right Bundle Branch Block0 (0)1 (4)1.00QTc prolongation8 (33)1 (4)0.02Myocardial infarction0 (0)1 (4)1.00Cardiac arrest1 (4)0 (0)0.48Other cardiac adverse events1 (4)1 (4)1.0Laboratory abnormalitiesAnemia18 (75)18 (69)0.89Leukopenia2 (8)2 (8)1.0Thrombocytopenia2 (8)4 (15)0.74Elevated aminotransferase2 (8)4 (15)0.74Raised Creatinine3 (13)6 (23)0.55Hyperkalemia2 (8)6 (23)0.48Hypokalemia17 (71)20 (77)0.87Hyponatremia18 (75)23 (88)0.39 *p-Values were not corrected for multiple testing. Three patients in the tamoxifen arm had grade 3 or 4 ventricular extra-systole events compared with none in the control arm (p=0.21). A 33-year-old male patient who had received tamoxifen suffered a cardiorespiratory arrest following a convulsion on day 21 of the study. He had no history of pre-existing cardiac disease. His ECG on admission had been normal with a QTc of 409 ms, and when performed routinely on the morning of day 21 showed mild sinus bradycardia (57 beats/minute) and a QTc interval of 477 ms. The arrest was not associated with ventricular arrhythmia although he had had grade 3 prolongation of QTc during the first 14 days of the study, which had resolved following tamoxifen interruption. Microbiology and susceptiblity testing All HIV infected patients, and seven HIV uninfected patients, had meningitis due to Cryptococcus neoformans molecular group VNI. Three HIV uninfected patients had disease due to Cryptococcus gattii (VGI). All isolates underwent susceptibility testing. The MIC90 of amphotericin B and fluconazole were 2 mg/L and 4 mg/L, respectively. The MIC90 of tamoxifen was 8 mg/L. We estimated the presence of drug interactions by calculating the fractional inhibitory concentration index (FICI) for each isolate. This was ≤0.5 (suggestive of a possible synergistic interaction) for tamoxifen combined with amphotericin in six isolates (12%), and for tamoxifen combined with fluconazole in two isolates (4%). Discussion We wanted to determine whether tamoxifen could be repurposed as an affordable treatment for cryptococcal meningitis. Our study was powered to detect an increase in the rate of yeast clearance of at least −0.11 log10 CFU/ml/day when tamoxifen was added to standard of care therapy. Differences of this order of magnitude are associated with improved survival in patients in low-income settings (Day et al., 2013; Molloy et al., 2018; Beardsley et al., 2016). Despite having previously shown that tamoxifen had activity in vitro against historical clinical isolates of C. neoformans, we found its addition had no impact on EFA. Therefore we do not believe that proceeding to a larger trial, powered to survival, is justified. It is not clear why tamoxifen did not provide benefit in our patients. The susceptibilities of the Cryptococcus isolates from this study to tamoxifen, fluconazole, and amphotericin, were similar to those of isolates from our previous clinical trials (Hai et al., 2019; O'Connor et al., 2020). However, in contrast with our previous findings we found evidence of synergy when tamoxifen was combined with amphotericin in only 12% (95CI 5%, 24%) of isolates from the trial. This compares with the rate in archived isolates of 67% (95CI 47%, 81%) (Hai et al., 2019). Synergy has been suggested as an explanation for the superiority of the amphotericin-flucytosine combination which has delivered improved yeast clearance and survival in a number of trials (Schwarz et al., 2003). In this study, we lack sufficient numbers of isolates where tamoxifen-amphotericin synergy is seen to be able to determine whether synergy per se influences EFA. A second potential explanation is that we may have failed to attain sufficient concentrations of tamoxifen in our patients. We chose a dose of 300 mg/day, based upon the MIC90 of tamoxifen against our historical isolates (16 mg/L) and the expected plasma concentrations this would achieve. Given that tamoxifen is concentrated in the brain (10- to 100-fold), and in macrophage phagosomes, we consider it unlikely that we did not reach drug concentrations greater than the MIC90 at the disease site, although it is possible that absorption of orally administered drug was impaired in our patients. The rates of adverse events in our study were similar between patients receiving tamoxifen and those in the control arm. Our study was powered to detect a difference in the rate of clearance of yeast from CSF and therefore may have lacked power to detect differences in rates of rarer adverse events. However, there was greater prolongation of the QTc interval in patients on tamoxifen. The mechanism through which tamoxifen causes QT interval prolongation in humans is unknown. In animals there is evidence that the block is multi-channel, due to both inhibition of the IKR and ICa channels (Asp et al., 2013; He et al., 2003; Liu et al., 1998). Such multi-channel block is considered to confer a reduced risk of life-threatening arrhythmias compared with drugs that block single ion channels. While we did not have any cases of ventricular tachycardia in our study, there was an episode of cardiac arrest in the tamoxifen arm. There are multiple potential causes of cardiac arrest in patients with cryptococcal meningitis, including intracranial pathology and electrolyte disturbances. The cardiac arrest in our study occurred on day 21, 1 week after administration of tamoxifen had finished. However, given tamoxifen’s half-life of 5 to 7 days, and the doses used, it is possible that this event was related. Fluconazole is also a recognised cause of QT prolongation. Here, the mechanism is believed to be through modulation of the Ikr cur