Literature DB >> 23736025

Risk of infections in renal cell carcinoma (RCC) and non-RCC patients treated with mammalian target of rapamycin inhibitors.

M D Kaymakcalan1, Y Je, G Sonpavde, M Galsky, P L Nguyen, D Y C Heng, C J Richards, T K Choueiri.   

Abstract

BACKGROUND: Mammalian target of rapamycin (mTOR) inhibitors are used in a variety of malignancies. Infections have been reported with these drugs. We performed an up-to-date meta-analysis to further characterise the risk of infections in cancer patients treated with these agents.
METHODS: Pubmed and oncology conferences' proceedings were searched for studies from January 1966 to June 2012. Studies were limited to phase II and III randomised controlled trials (RCTs) of everolimus or temsirolimus reporting on cancer patients with adequate safety profiles. Summary incidences, relative risks (RRs), and 95% confidence intervals (CIs) were calculated.
RESULTS: A total of 3180 patients were included. The incidence of all-grade and high-grade infections due to mTOR inhibitors was 33.1% (95% CI, 24.5-43.0%) and 5.6% (95% CI, 3.8-8.3%), respectively. Compared with controls, the RR of all-grade and high-grade infections due to mTOR inhibitors was 2.00 (95% CI, 1.76-2.28, P<0.001) and 2.60 (95% CI, 1.54-4.41, P<0.001), respectively. Subgroup analysis found no difference in incidences or risks between everolimus and temsirolimus or between different tumour types (renal cell carcinoma (RCC) vs non-RCC). Infections included respiratory tract (61.7%), genitourinary (29.4%), skin/soft tissue (4.2%), and others (4.9%).
CONCLUSION: Treatment with mTOR inhibitors is associated with a significant increase in risk of infections. Close monitoring for any signs of infections is warranted.

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Year:  2013        PMID: 23736025      PMCID: PMC3694254          DOI: 10.1038/bjc.2013.278

Source DB:  PubMed          Journal:  Br J Cancer        ISSN: 0007-0920            Impact factor:   7.640


Mammalian target of rapamycin (mTOR) inhibitors are targeted agents that have developed into an important therapeutic drug class used in a variety of malignancies. Everolimus (Afinitor, Novartis Pharmaceuticals, East Hanover, NJ, USA) is currently approved by the Food and Drug Administration (FDA) for the treatment of several malignancies including advanced renal cell carcinoma (RCC; Motzer , 2010), progressive pancreatic neuroendocrine tumours (PNET; Yao ), subependymal giant cell astrocytomas associated with tuberous sclerosis (Krueger ) and most recently in combination with exemestane for advanced hormone receptor-positive, HER-2-negative breast cancer (Baselga ). Temsirolimus (Torisel, Pfizer, New York, NY, USA) is approved by the FDA for the indication of advanced RCC (Hudes ). This class of agents inhibits tumour cell proliferation by first binding to an intracellular protein (FKBP-12), which results in a protein–drug complex with mTOR, thereby inhibiting phosphorylation of p70S6 kinase and S6 ribosomal protein in the PI3 kinase/AKT pathway (Nashan, 2002; Abraham and Gibbons, 2007). This process ultimately leads to the downregulation of hypoxia inducible factor genes, including vascular endothelial growth factor, necessary for cancer cell growth, survival, and angiogenesis (Thomas ). Mammalian target of rapamycin inhibitors do not usually produce the systemic toxicities that are traditionally seen with chemotherapy such as nausea, vomiting, alopecia, and bone marrow suppression. However, as more targeted agents are developed their different class-specific toxicities are emerging. Trials exploring the safety and efficacy of everolimus and temsirolimus reported some unique side effects including rash, mucositis, infection, pneumonitis, hyperlipidaemia, and hyperglycaemia (Hutson ; Ravaud, 2011; Elsen ). Specifically, infections were reported in both everolimus and temsirolimus trials as a common side effect, as a cause of treatment disruption, and in some cases led to fatalities (Galanis ; Ansell ; Krueger ; Motzer ; Sakaria ; Tarhini ; Budde ; Choueiri ). The association of infection with mTOR inhibitors and its possible clinical significance warrants further characterisation. We sought out to assess the magnitude of this problem by looking at the incidence and risk of infections in patients receiving mTOR inhibitors in a large, up-to-date meta-analysis of randomised control trials.

Materials and methods

Study selection

An independent review of the Pubmed databases from January 1966 to June 2012 was conducted. Searches were performed, limited to only human studies, with either the key terms ‘everolimus,' ‘Afinitor,' ‘RAD-001' or ‘temsirolimus,' ‘Torisel,' ‘CCI-779.' Citations investigating mTOR inhibitors in a non-oncological setting were excluded. Potentially relevant abstracts were collected and independently coded by four investigators (MDK, GS, CJR, and TKC). The full texts of the selected abstracts were obtained and analysed for appropriate trial design and safety reporting. Only randomised phase II or III studies with a placebo/control arm were used in order to properly calculate relative risk (RR). The Jadad scale was used to assess study quality based on study randomisation, double-blinding practice, and handling of withdrawals (Jadad ). When more than one publication was drawn from the same clinical trial, the most recent or most complete report was used. The most recent package insert for each agent was assessed for the most current clinical information, and the manufacturer and/or the overall investigator was contacted to obtain clarification on infection information. The process was duplicated using the same search terms and limitations in the American Society of Clinical Oncology online databases of meeting abstracts from 2000 to 2012.

Data extraction

Data extraction was conducted according to the Preferred Reporting Items for Systemic Reviews of Meta-Analyses statement (Moher ). Any discrepancies between reviewers' classifications of publications were resolved by consensus. The following information was extracted from each study: first author's name, year of publication, trial phase, underlying malignancy, number of enrolled patients, treatment arms, median age and range, median treatment duration and range, median overall survival and 95% confidence interval (CI), number of patients available for analysis, number of all-grade infections attributed to study drug, and number of high-grade infections attributed to study drug. All-grade and high-grade infections were defined according to the National Cancer Institute Common Toxicity Criteria version 3.0 in all trials used for the analysis.

Statistical analysis

We extracted the number of patients with all-grade and high-grade infections and the number of patients who were treated with mTOR inhibitors or control from the selected clinical trials to calculate incidence. The proportion of patients with all-grade infections and 95% CIs were derived from each trial. RRs and 95% CIs were also calculated by comparing the incidence of all-grade infection in patients assigned to mTOR inhibitors with the incidence among controls in the same trial. For studies reporting zero events in a treatment or control arm, we applied a classic half-integer continuity correction to calculate the RR and variance. We then repeated this for high-grade infections. Statistical heterogeneity among trials included in the meta-analysis was evaluated using Cochrane's Q statistic (Cochran, 1954), and inconsistency was quantified with the I2 statistic that estimates the percentage of total variation across studies due to heterogeneity rather than chance (Higgins ). The assumption of homogeneity was considered invalid for P-values<0.1. To calculate the summary incidence or RRs of all-grade or high-grade infections, we combined trial-specific estimates using random-effects or fixed-effects models depending on the heterogeneity of included trials. When no substantial heterogeneity among trials was found, the summary estimate calculated on the basis of the fixed-effects model was reported by using the inverse variance method. When substantial heterogeneity among trials was observed, the summary estimate calculated on the basis of the random-effects model was reported by using the DerSimonian and Laird (1986) method that considers both within-study and between-study variations. For trials with multiple treatment groups examining varying doses of mTOR inhibitors, we combined the treatment groups for the overall analysis. To explore the possible reasons for the heterogeneity, we conducted meta-regression analyses to see whether there was a variation in risk estimates by type of drug, underlying malignancy, type of trial, and Jadad score. In addition, we conducted sensitivity analyses by omitting one study at a time to see the influence of each trial on the overall effect estimate. Finally, publication bias was evaluated through funnel plots (that is, plots of study results against precision) and with the Begg's and Egger's test (Begg and Mazumdar, 1994; Egger ). A two-tailed P-value of <0.05 was considered statistically significant. All statistical analyses were performed using Stata SE version 12.0 software (Stata Corporation, College Station, TX, USA).

Results

Population characteristics

Our initial search yielded a total of 366 potentially relevant abstracts in Pubmed, with 309 abstracts searching for everolimus studies and 57 abstracts searching for temsirolimus studies. Two hundred and thirty-five everolimus studies were immediately excluded for not being oncological studies. One study from the temsirolimus search was excluded for not relating to an mTOR-inhibiting drug. Subsequently, an additional 118 studies were excluded for one of the following reasons: non-randomised trials, phase I trials, commentaries, review articles, editorials, letters, or only study design reporting. Four everolimus studies were excluded for being duplicates or subgroup-only analyses of previously reported trial data (Motzer ; Beaumont ; Calvo ; Tsukamoto ). The remaining eight trials, including five studies with everolimus (Baselga ; Motzer ; Pavel ; Yao ; Baselga ) and three studies with temsirolimus (Hudes ; Hess ; Negrier ), were selected for the meta-analysis. Of the eight selected trials, six were phase III and two were phase II trials as shown in the selection process outlined in Figure 1. The baseline characteristics of each trial are presented in Table 1. There were 2233 patients from the everolimus trials and 947 patients from the temsirolimus trials for a total of 3180 patients available for safety analysis. The selected trials investigated patients with RCC (Hudes ; Motzer ; Negrier ), hormone receptor-positive breast cancer (Baselga , 2012), PNET (Yao ), all types of neuroendocrine tumours (Pavel ), and mantle cell lymphoma (Hess ) (Table 1). Inclusion criteria typically required that patients had good performance status and no active baseline infection, as well as adequate bone marrow, hepatic, pulmonary, and renal functions.
Figure 1

Selection process for randomised controlled trials included in the meta-analysis.

Table 1

Baseline characteristics of the included trials in the meta-analysis

 
 
 
 
 
 
 
 
 
 
No. of infections as a result of study drug
 
Author, yearPhaseHistologyPatients enrolledTreatment arms/doseMedian age (years)(range)Median treatment duration (months)(Range)Median OS (months)(range)Median PFS (months)(range)Patients for safety analysisAll gradeHigh gradeReported all-grade infectionsQuality
Everolimus
Baselga et al, 20123HR(+) BC724Everolimus 10 mg QD+exemestane 25 mg QDPlacebo+exemestane 25 mg QD62 (34–93)61 (28–90)6.03.3Not reachedNot reached114.148223824159244Resp, GU, sepsis, candida, hepatits C5
Baselga et al, 20092HR(+) BC270Everolimus 10 mg QD+letrozole 25 mg QDPlacebo+letrozole 2.5 mg QD69 (46–88)67 (43–84)Not ReportedNot ReportedN/AN/AN/AN/A1371323211Resp, skin/soft tissue5
Motzer et al, 20103RCC416Everolimus 10 mg QDPlacebo61 (27–85)60 (29–79)4.7 (0.63–15)2 (0.7–6.5)14.814.44.9 (4.0–5.5)1.9 (1.8–1.9)27413710124271Resp, GU, sepsis, candida aspergillosis5
Pavel et al, 20113NET429Everolimus 10 mg QD+octreotide 30 mg Q28DPlacebo+octreotide 30 mg Q28D60 (22–83)60 (27–81)9.2 (0.25–40.7)9.1 (<0.25–38)Not reachedNot reached16.4 (13.7–21.2)11.3 (8.4–14.6)2152114213111NOS5
Yao et al, 2011
3
PNET
410
Everolimus 10 mg QDPlacebo
58 (23–87)57 (20–82)
9.24
Not reachedNot reached
13.7 (11.2–18.8)5.7 (5.4–8.3)
204203
8338
01
Resp, GU
5
Temsirolimus
Hess et al, 20093MCL162Temsirolimus 175 mg followed by 75 mg QWTemsirolimus 175 mg followed by 25 mg QWInvestigator's choice of therapy68 (44–87)68.5 (43–85)64.5 (39–88)3 (0.25–24.4)3.5 (0.25–43)5 (0.25–8.7)12.8 (8.6–19.3)10 (7.2–14.6)9.7 (5.8–15.1)4.8 (3.1–8.1)3.4 (1.9–5.5)1.9 (1.6–2.5)54545315114422NOS3
Hudes et al, 20073RCC626Temsirolimus 25 mg QWINF-α 3 mIU–18 mIU TIWTemsirolimus 15 mg QW+INF-α 6 mIU TIW58 (32–81)60 (23–86)59 (32–82)3.8 (3.5–3.9)1.9 (1.9–2.2)2.5 (1.9–3.6)10.9 (8.6–12.7)7.3 (6.1–8.8)8.4 (6.6–10.3)5.5 (3.9–7.0)3.1 (2.2–3.8)4.7 (3.9–5.8)20820020811850709722Resp, GU3
Negrier et al, 20112RCC171Temsirolimus 25 mg QW+bevacizumab 10 mg kg−1 Q2WSunitinb 50 mg Q6W days 1–28INF-α 9 mIU TIW+bevacizumab 10 mg kg−1 Q2W62 (33–83)61.2 (33–83)61.9 (40–79)5.1 (0–12)10.4 (0.5–12)7.2 (1.0–12)Not reachedNot reachedNot reached8.2 (7.0–9.6)8.2 (5.5–11.7)16.8 (6.0–26)884240511612N/AN/AN/AResp, GU, skin/soft tissue, GI, sepsis, fungal, Candida, herpes, parasitic3

Abbreviations: GI=gastrointestinal; GU=genitourinary; HR(+) BC=hormone receptor-positive breast cancer; INF-α=interferon alpha; MCL=mantle cell lymphoma; mIU=million international units; NET=neuroendocrine tumour; No.=number; NOS=not otherwise specified; OS=overall survival; PFS=progression-free survival; PNET=pancreatic neuroendocrine tumour; QD=once a day; QW=once a week; Q28D=once a month; Q2W=twice weekly; Q6W=every 6 weeks; RCC=renal cell carcinoma; Resp=respiratory; TIW=three times a week.

Overall incidence and types of infection

All mTOR inhibitor treatment arms were included in the analysis to calculate the overall incidence of infections. All-grade infections due to mTOR inhibitors occurred in 735 patients, representing an incidence of 33.1% (95% CI, 24.5–43.0%), whereas high-grade infections occurred in 100 patients, representing an incidence of 5.6% (95% CI, 3.8–8.3%). When subgrouped by drug type, the incidence of all-grade infections was 27.1% (95% CI, 16.5–41.0%) for everolimus and 41.8% (95% CI, 26.6–58.7%) for temsirolimus. For high-grade infection, the incidence for everolimus was 4.5% (95% CI, 2.3–8.6%) and the incidence for temsirolimus was 7.1% (95% CI, 5.2–9.7%). The incidence for the placebo/control arm was 15.5% (95% CI, 10.2–22.8%) for all-grade infections and was 1.6% (95% CI, 0.8–3.1%) for high-grade infections. All of the studies used in the meta-analysis documented the rates of both all-grade and high-grade infections, with the exception of one temsirolimus study that did not indicate the incidence of high-grade infections. There were 262 (35.6%) reported infections on mTOR inhibitors in which the type of the infection was not otherwise specified in the studies. Of the six studies that reported on the underlying type of infection (N=473), the most common were respiratory tract infections, representing 292 patients or 61.7% of all infections due to mTOR inhibitors. Genitourinary infections (29.4%), skin/soft tissue infections (4.2%), sepsis (1.5%), and gastrointestinal infections (0.2%) were the other infections that were reported in the studies (Table 1). Fungal infections, including candida (1.3%), aspergillosis (0.4%), and others (0.2%) were reported in the studies. Viral infections, including herpes (1.1%) and hepatitis (0.2%), and parasitic infections (0.2%) were also reported (Table 1). Some of these infections were severe and led to the most common cause of fatal adverse events in the trials (Choueiri ).

RRs of infections and subgroup analysis

All eight trials (five everolimus+three temsirolimus) reported the incidence of all-grade infections and seven trials (five everolimus+two temsirolimus) reported the incidence of high-grade infections, which were used to calculate the RRs of infections associated with mTOR inhibitor use. The overall RR of developing an all-grade infection for mTOR inhibitors vs control was 2.00 (95% CI, 1.76–2.28, P<0.001). No significant heterogeneity was found among the trials (Q=5.02, I2=0.0%, P=0.658; Figure 2). By drug type, everolimus-treated patients (5 trials, 1312 patients) had an increased risk of all-grade infection, with a RR of 2.14 (95% CI, 1.81–2.53, P<0.001), and temsirolimus-treated patients (3 trials, 612 patients) had an increased risk of all-grade infection, with a RR of 1.81 (CI 95%, 1.48–2.22, P<0.001). Comparing the RRs of everolimus with temsirolimus demonstrated no significant difference (P=0.26; Table 2).
Figure 2

Relative risks of all-grade and high-grade infections associated with mTOR inhibitors.

Table 2

Incidences and relative risks of all-grade and high-grade infections associated with mTOR inhibitors

  
No. of infection/No. of subjects
Incidence
 
 Number of studiesmTOR inhibitorsPlacebomTOR inhibitorsPlaceboRelative risk (95% CI)Test for heterogeneity
All grade
Overall8735/1924218/125633.1% (24.5–43.0)15.5% (10.2–22.8)2.00 (1.76–2.28); P<0.001Q=5.02, P=0.658, I2=0.0%
Everolimus5470/1312136/92127.1% (16.5–41.0)12.2% (6.8–21.1)2.14 (1.81–2.53); P<0.001Q=2.13, P=0.711, I2=0.0%
Temsirolimus
3
265/612
82/335
41.8% (26.6–58.7)
22.2% (12.4–36.5)
1.81 (1.48–2.22); P<0.001
Q=1.36, P=0.506, I2=0.0%
High grade
Overall7100/183617/11745.6% (3.8–8.3)1.6% (0.8–3.1)2.60 (1.54–4.41); P<0.001Q=7.41, P=0.284, I2=19.1%
Everolimus563/13128/9214.5% (2.3–8.6)1.0% (0.5–2.0)3.63 (1.66–7.94); P=0.001Q=5.97, P=0.202, I2=32.9%
Temsirolimus237/5249/2537.1% (5.2–9.7)3.6% (1.9–6.7)1.97 (0.97–4.03); P=0.062Q=0.17, P=0.681, I2=0.0%

Abbreviations: CI=confidence interval; mTOR=mammalian target of rapamycin; No.=number.

When considering only high-grade infection events, the overall RR for mTOR inhibitors vs control was 2.60 (CI 95%, 1.54–4.41, P<0.001). No significant heterogeneity was found among the studies reporting high-grade infections (Q=7.41, I2=19.1%, P=0.284) (Figure 2). By drug type, everolimus-treated patients (5 trials, 1,312 patients) had an increased risk of high-grade infection, with a RR of 3.63 (95% CI, 1.66–7.94, P=0.001). Temsirolimus-treated patients (2 trials, 524 patients) tended to have an increased risk of a high-grade infection, but the RR for temsirolimus vs control (RR=1.97; 95% CI, 0.97–4.03, P=0.062) did not reach a level of statistical significance because of smaller numbers. No significant differences were observed when comparing the RRs of high-grade infection between everolimus and temsirolimus (P=0.35; Table 2). To determine whether the observed increases in RRs of all-grade and high-grade infections were influenced by tumour type, we performed a subgroup analysis of RCC, the most commonly occurring malignancy (3 studies and 1197 total patients or 37.6% of all patients), vs all other malignancies. The RR of all-grade infection in patients treated with RCC was 1.84 (95% CI, 1.53–2.21; P<0.001), whereas the RR of all-grade infection in patients with other malignancies (five trials) was 2.18 (95% CI, 1.82–2.60; P<0.001). No significant difference was observed in RRs of all-grade infection between the patients with RCC or non-RCC (P=0.25). Similarly, the RR of high-grade infection in patients with RCC treated with mTOR inhibitors (two trials) was 2.76 (95% CI, 1.31–5.81; P=0.007). For non-RCC patients (five trials), the RR of all-grade infection was 2.46 (95% CI, 1.16–5.19; P=0.018). No difference was found when comparing the RRs of high-grade infection in patients having RCC with other malignancies (P=0.63; Table 2).

Study quality

Randomised treatment allocation sequences were generated in all trials used in the analysis. All five everolimus trials were double-blinded, placebo-controlled, and of highest quality achieving the highest Jadad score of 5. All three temsirolimus trials were not double-blinded nor placebo-controlled, but they did all have active treatment controls. All studies were of good methodological quality according to the 5-point Jadad score (all trials ⩾3). To further assess study quality, we also compared the RRs of all-grade and high-grade infection among phase II vs phase III trials. There were no statistically significant differences between the phase subgroups for either grade (all-grade P=0.33; high-grade P=0.57). To assess the influence of each study on the overall RRs of all-grade and high-grade infection, we performed a sensitivity analysis by omitting one study at a time and found that there were no studies that had a significant impact on the overall RR. Finally, we attempted to assess the possible association between risk of infection and increased exposure to mTOR inhibitors. In convention with other studies, we calculated the mean of the median durations of therapy as a cut-off, which was found to be 5.8 months. When comparing the RRs of all-grade and high-grade infections due to mTOR inhibitors amongst long-coursed trials and short-coursed trials, we did not observe a statistically significant difference (all-grade P=0.33; high-grade P=0.80).

Publication bias

The Begg's test and the Egger's test were conducted on the incidence and RR of all-grade infection, and both showed no evidence of publication bias (for RR of all-grade infection, Begg's P=0.54 and Egger's P=0.31). Similarly, the Begg's and Egger's tests were performed on the incidence and RR of high-grade infection, and no evidence of publication bias was found (for RR of high-grade infection, Begg's P=0.55 and Egger's P=0.97).

Discussion

Our meta-analysis combined eight RCTs investigating mTOR inhibitors for the treatment of cancers. To our knowledge, this is the first large study of RCTs demonstrating a significant increase in the risk of infection with the use of mTOR inhibitors in cancer patients. Our analysis found that the risk of developing an infection of any grade was two-fold higher in patients treated with mTOR inhibitors. And, more importantly, there is a 2.6-fold increase in the risk of high-grade infection associated with the use of mTOR inhibitors. The observed infection risk can possibly be explained by the potential immunosuppressant effects of mTOR inhibitors. Everolimus and sirolimus, the principal active metabolite of temsirolimus, are known to inhibit interleukin (IL)-2-, IL-7-, and IL-15-driven proliferation of activated T cells and B cells (Lai and Tan, 1994; Schuler ; Shegal, 2003; Chapman and Perry, 2004). Although there were no statistically significant differences between temsirolimus and everolimus when comparing their RRs, there was a heavier contribution from everolimus to the RR of infection, likely because of the larger number of everolimus patients and studies used in the analysis rather than a distinctive quality of the drug. With an increased RR of treatment-related infections, it is clear that proper monitoring, immediate intervention, and effective management is crucial to achieve the maximal therapeutic benefit of mTOR inhibitors. After reporting the incidence of infection in everolimus-treated RCC patients, which was similar to the incidence in our analysis (37% vs 33.1% Motzer ), the RECORD-1 Study Group subsequently published recommendations for the management of infections and other adverse events according to the grade of the event (Porta ; Ravaud, 2011). These recommendations can be used by clinicians to effectively manage treatment-related infections. Fungal infections such as Candida and Aspergillosis, mycobacterial infections such as tuberculosis, and viral infections such as hepatitis and herpes occurred in the studies used in our analysis and were reported in the prescribing information (Novartis, 2012; Pfizer, 2012). Patients must be appropriately screened for viral, mycobacterial and fungal infections in the right clinical context. Clinicians must fully treat patients with any active infection before the initiation of mTOR inhibitors and must monitor patients during the course of treatment (Porta ). Typically, patients with active or recently active infections are excluded from clinical trials; therefore, the true incidence of these infections could be widely under-reported. More trials and reporting on these patients must be done in order to gain more insight into the management of this subgroup of patients. A randomised, double-blinded multicenter trial evaluated the pharmacokinetics of temsirolimus and suggested that there may indeed be a correlation between the cumulative exposure of temsirolimus and certain adverse effects including infection (Boni ). In our meta-analysis, patients in the studies with longer treatment durations did not have more risk to develop infections than patients on studies with shorter treatment durations (P>0.05 for all-grade and high-grade). The findings do not support the association of infection risk and cumulative exposure; however, information on the time of occurrence of infection and individual data points on treatment duration may be needed to properly investigate the association. Despite the size of this meta-analysis, our study has several limitations. First, we only had access to the available data published in the clinical trials, so there were patient variables that were not known, such as co-morbidities, previous treatment exposure, concomitant medications, and dose interruptions. Second, patients in trials have adequate organ and haematological function, which may not be the case in common oncology practice. It is conceivable that the true incidence and risk of treatment-related adverse effects is higher in actual practice. Third, not all of the included studies were double-blinded, but blinding is not always possible with parenteral administration. Although some of the included studies were not blinded, they were all of good methodological quality. Lastly, and despite our attempts, the reported safety data did not disclose the specific aetiologies of all the infections that occurred. In conclusion, the mTOR inhibitors everolimus and temsirolimus are associated with an increased risk of all-grade and high-grade infections. These targeted agents are of great clinical benefit in various malignancies and the benefits outweigh the risks in the vast majority of cases, and thus their FDA approval. However, the immediate detection and effective management of the potential bacterial, viral, and fungal infections that can occur with these agents is crucial for optimal patient outcomes.
  36 in total

1.  Everolimus in postmenopausal hormone-receptor-positive advanced breast cancer.

Authors:  José Baselga; Mario Campone; Martine Piccart; Howard A Burris; Hope S Rugo; Tarek Sahmoud; Shinzaburo Noguchi; Michael Gnant; Kathleen I Pritchard; Fabienne Lebrun; J Thaddeus Beck; Yoshinori Ito; Denise Yardley; Ines Deleu; Alejandra Perez; Thomas Bachelot; Luc Vittori; Zhiying Xu; Pabak Mukhopadhyay; David Lebwohl; Gabriel N Hortobagyi
Journal:  N Engl J Med       Date:  2011-12-07       Impact factor: 91.245

2.  Incidence and risk of treatment-related mortality in cancer patients treated with the mammalian target of rapamycin inhibitors.

Authors:  T K Choueiri; Y Je; G Sonpavde; C J Richards; M D Galsky; P L Nguyen; F Schutz; D Y Heng; M D Kaymakcalan
Journal:  Ann Oncol       Date:  2013-05-08       Impact factor: 32.976

Review 3.  Management of adverse events associated with the use of everolimus in patients with advanced renal cell carcinoma.

Authors:  Camillo Porta; Susanne Osanto; Alain Ravaud; Miguel-Angel Climent; Ulka Vaishampayan; Dorothy A White; Patricia Creel; Brenda Dickow; Patricia Fischer; Suzanne Sweeney Gornell; Federica Meloni; Robert J Motzer
Journal:  Eur J Cancer       Date:  2011-04-08       Impact factor: 9.162

Review 4.  Treatment-associated adverse event management in the advanced renal cell carcinoma patient treated with targeted therapies.

Authors:  Alain Ravaud
Journal:  Oncologist       Date:  2011

5.  Everolimus in metastatic renal cell carcinoma: Subgroup analysis of patients with 1 or 2 previous vascular endothelial growth factor receptor-tyrosine kinase inhibitor therapies enrolled in the phase III RECORD-1 study.

Authors:  E Calvo; B Escudier; R J Motzer; S Oudard; T E Hutson; C Porta; S Bracarda; V Grünwald; J A Thompson; A Ravaud; D Kim; A Panneerselvam; O Anak; R A Figlin
Journal:  Eur J Cancer       Date:  2011-12-30       Impact factor: 9.162

6.  Everolimus plus octreotide long-acting repeatable for the treatment of advanced neuroendocrine tumours associated with carcinoid syndrome (RADIANT-2): a randomised, placebo-controlled, phase 3 study.

Authors:  Marianne E Pavel; John D Hainsworth; Eric Baudin; Marc Peeters; Dieter Hörsch; Robert E Winkler; Judith Klimovsky; David Lebwohl; Valentine Jehl; Edward M Wolin; Kjell Öberg; Eric Van Cutsem; James C Yao
Journal:  Lancet       Date:  2011-11-25       Impact factor: 79.321

7.  Temsirolimus and bevacizumab, or sunitinib, or interferon alfa and bevacizumab for patients with advanced renal cell carcinoma (TORAVA): a randomised phase 2 trial.

Authors:  Sylvie Négrier; Gwenaëlle Gravis; David Pérol; Christine Chevreau; Rémy Delva; Jacques-Olivier Bay; Ellen Blanc; Céline Ferlay; Lionnel Geoffrois; Frédéric Rolland; Eric Legouffe; Emmanuel Sevin; Brigitte Laguerre; Bernard Escudier
Journal:  Lancet Oncol       Date:  2011-06-12       Impact factor: 41.316

Review 8.  Targeted therapies for renal cell carcinoma: review of adverse event management strategies.

Authors:  Tim Eisen; Cora N Sternberg; Caroline Robert; Peter Mulders; Lynda Pyle; Stephan Zbinden; Hassan Izzedine; Bernard Escudier
Journal:  J Natl Cancer Inst       Date:  2012-01-10       Impact factor: 13.506

9.  Everolimus for advanced pancreatic neuroendocrine tumors.

Authors:  James C Yao; Manisha H Shah; Tetsuhide Ito; Catherine Lombard Bohas; Edward M Wolin; Eric Van Cutsem; Timothy J Hobday; Takuji Okusaka; Jaume Capdevila; Elisabeth G E de Vries; Paola Tomassetti; Marianne E Pavel; Sakina Hoosen; Tomas Haas; Jeremie Lincy; David Lebwohl; Kjell Öberg
Journal:  N Engl J Med       Date:  2011-02-10       Impact factor: 91.245

Review 10.  Sirolimus: its discovery, biological properties, and mechanism of action.

Authors:  S N Sehgal
Journal:  Transplant Proc       Date:  2003-05       Impact factor: 1.066

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  12 in total

1.  Improving consolidation therapy in acute myeloid leukemia - a tough nut to crack.

Authors:  Richard F Schlenk; Sonia Jaramillo; Carsten Müller-Tidow
Journal:  Haematologica       Date:  2018-10       Impact factor: 9.941

2.  Interstitial lung disease during targeted therapy in metastatic renal cell carcinoma: a case series from three centres.

Authors:  Philipp Ivanyi; Thomas Fuehner; Meike Adam; Christian Eichelberg; Edwin Herrmann; Axel Stuart Merseburger; Arnold Ganser; Viktor Grünwald
Journal:  Med Oncol       Date:  2014-08-15       Impact factor: 3.064

3.  Clinically-Relevant Rapamycin Treatment Regimens Enhance CD8+ Effector Memory T Cell Function In The Skin and Allow their Infiltration into Cutaneous Squamous Cell Carcinoma.

Authors:  Ji-Won Jung; Margaret Veitch; Jennifer A Bridge; Nana H Overgaard; Jazmina L Cruz; Richard Linedale; Michael E Franklin; Nicholas A Saunders; Fiona Simpson; Ian H Frazer; Raymond J Steptoe; James W Wells
Journal:  Oncoimmunology       Date:  2018-07-30       Impact factor: 8.110

4.  Higher Risk of Infections with PI3K-AKT-mTOR Pathway Inhibitors in Patients with Advanced Solid Tumors on Phase I Clinical Trials.

Authors:  Saeed Rafii; Desamparados Roda; Elena Geuna; Begona Jimenez; Karim Rihawi; Marta Capelan; Timothy A Yap; L Rhoda Molife; Stanley B Kaye; Johann S de Bono; Udai Banerji
Journal:  Clin Cancer Res       Date:  2015-02-03       Impact factor: 12.531

Review 5.  Risk of Hyponatraemia in Cancer Patients Treated with Targeted Therapies: A Systematic Review and Meta-Analysis of Clinical Trials.

Authors:  Rossana Berardi; Matteo Santoni; Silvia Rinaldi; Emilia Nunzi; Alessia Smerilli; Miriam Caramanti; Francesca Morgese; Mariangela Torniai; Agnese Savini; Ilaria Fiordoliva; Azzurra Onofri; Mirco Pistelli; Augusto Taccaliti; Stefano Cascinu
Journal:  PLoS One       Date:  2016-05-11       Impact factor: 3.240

6.  Addition of the mammalian target of rapamycin inhibitor, everolimus, to consolidation therapy in acute myeloid leukemia: experience from the UK NCRI AML17 trial.

Authors:  Alan K Burnett; Emma Das Gupta; Steve Knapper; Asim Khwaja; Marion Sweeney; Lars Kjeldsen; Timothy Hawkins; Sophie E Betteridge; Paul Cahalin; Richard E Clark; Robert K Hills; Nigel H Russell
Journal:  Haematologica       Date:  2018-07-05       Impact factor: 9.941

Review 7.  Infections associated with immunotherapeutic and molecular targeted agents in hematology and oncology. A position paper by the European Conference on Infections in Leukemia (ECIL).

Authors:  Georg Maschmeyer; Julien De Greef; Sibylle C Mellinghoff; Annamaria Nosari; Anne Thiebaut-Bertrand; Anne Bergeron; Tomas Franquet; Nicole M A Blijlevens; Johan A Maertens
Journal:  Leukemia       Date:  2019-01-30       Impact factor: 11.528

Review 8.  Immunomodulation and Disease Tolerance to Staphylococcus aureus.

Authors:  Zhigang Li; Adam G Peres; Andreea C Damian; Joaquín Madrenas
Journal:  Pathogens       Date:  2015-11-13

Review 9.  Risk of Infectious Complications in Hemato-Oncological Patients Treated with Kinase Inhibitors.

Authors:  Mark Reinwald; Tobias Boch; Wolf-Karsten Hofmann; Dieter Buchheidt
Journal:  Biomark Insights       Date:  2016-04-21

10.  mTOR inhibitors lower an intrinsic barrier to virus infection mediated by IFITM3.

Authors:  Guoli Shi; Stosh Ozog; Bruce E Torbett; Alex A Compton
Journal:  Proc Natl Acad Sci U S A       Date:  2018-10-09       Impact factor: 11.205

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