Self-Reported Conflicts of Interest of Authors, Trial Sponsorship, and the Interpretation of Editorials and Related Phase III Trials in Oncology

2013 ◽  
Vol 31 (18) ◽  
pp. 2289-2295 ◽  
Author(s):  
Giovanni M. Bariani ◽  
Anezka C.R. de Celis Ferrari ◽  
Paulo M. Hoff ◽  
Monika K. Krzyzanowska ◽  
Rachel P. Riechelmann
Keyword(s):  
Cancer Research ◽  
Conflicts Of Interest ◽  
Multivariable Analysis ◽  
Phase Iii ◽  
Experimental Therapy ◽  
Phase Iii Trial ◽  
Research Reporting ◽  
Phase Iii Trials ◽  
Positive Results ◽  
Related Phase

Purpose Growing participation by industry in cancer research has resulted in increased reporting of conflicts of interest (COI). We aimed to test any association between authors' conclusions and self-reported COI or trial sponsorship in cancer studies. Methods Editorials and related phase III trials published in six clinical oncology journals in the last 3.5 years were analyzed independently by two investigators who classified study conclusions according to authors' endorsement of the experimental therapy. Logistic regression multivariable models were used to assess predictors of favorable conclusions of editorialists and of phase III authors. Results From January 2008 to October 2011, 1,485 articles were retrieved: 150 phase III trials and 150 editorials were eligible. Among the phase III trials, 82 (54.7%) had positive results, and 78 (52.0%) were entirely or partially funded by industry. Any COI were disclosed in 103 phase III trials (68.7%) and in 71 editorials (47.3%). Multivariable analysis showed that phase III trial results were the only significant predictor for a positive conclusion by trial authors (odds ratio [OR], 92.2; 95% CI, 19.7 to 431.6; P < .001). Sponsorship did not predict for positive conclusion by phase III authors (OR, 0.86; 95% CI, 0.3 to 2.5; P = .788). The only factor associated with positive conclusions by editorial authors was a positive conclusion by phase III trial authors (OR, 36.3; 95% CI, 6.8 to 194.2; P < .001). Conclusion The interpretation of recently published phase III cancer trials by their authors or by editorialists was not influenced by financial relationships or industry sponsorship. Increased awareness of COI policies may have led to more integrity in cancer research reporting.

Self-reported conflicts of interest (sfCOI) of authors and the interpretation of randomized phase III trials (RCT) and related editorials (REd) in cancer research.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 6055-6055
Author(s):  
Giovanni Mendonca Bariani ◽  
Anezka Carvalho Rubin De Celis Ferrari ◽  
Paulo Marcelo Hoff ◽  
Rachel Riechelmann
Keyword(s):  
Cancer Research ◽  
Logistic Regression ◽  
Conflicts Of Interest ◽  
Multivariable Analysis ◽  
Phase Iii ◽  
Experimental Therapy ◽  
Negative Results ◽  
Study Results ◽  
Phase Iii Trials ◽  
Cancer Studies

6055 Background: Growing participation from industry in cancer research has resulted in increased reporting of COI. We aimed to test any association between author’s conclusion and sfCOI in cancer studies. Methods: All RCT and REd published in 6 major cancer journals in a 3.5 year period were selected. Two investigators blinded to COI disclosure independently analyzed each RCT and REd, classifying authors’ conclusions as highly positive, positive, neutral, negative, and highly negative with respect to author’s opinion on the experimental therapy. The agreement rate between investigators for conclusion classification was 90% (consensus was achieved for the remaining 10%). We also collected data on study results, COI and sponsorship. COI was defined as any self-reported financial tie between author and industry except for research funds. Predictors of positive/highly positive conclusions of RCT and of REd were tested separately in logistic regression multivariable models. Results: From Jan 2008 to Oct 2011, 1,485 articles were retrieved: 150 RCT and 140 REd were eligible. Among the RCT, 82 (55%) were positive, and 78 (52%) were entirely or partially funded by industry. Any sfCOI was present in 103 (69%) RCT and in 71 (47%) REd. Conclusions of REd and RCT were: 7.3% and 11.3% highly positive, 42.7% and 57.3% positive, 8.0% and 2.0% neutral, 29.3% and 18.7% negative, and 12.7% and 10.7% highly negative, respectively. Multivariable analysis showed that RCT positive result was the only significant predictor for positive conclusion by RCT authors (OR=109, 95% CI: 21-567; p<0.001). The only factor associated with positive conclusions of REd authors was a positive conclusion by RCT author (OR=42, 95% CI: 7-244; p<0.001). While 64 (43%) RCT reported negative results, 103 (68.7%) RCT authors interpreted studies positively. Logistic regression for discordance between RCT result and RCT conclusion did not find any association with COI. Conclusions: The interpretation of RCT results by authors was not influenced by sfCOI or trial sponsorship. Authors of REd were not influenced by study results or by their sfCOI when discussing cancer RCT.

Learning from the Past: A Review of Clinical Trials Targeting Amyloid, Tau and Neuroinflammation in Alzheimer’s Disease

2020 ◽  
Vol 17 (2) ◽  
pp. 112-125 ◽  
Author(s):  
Kelly Ceyzériat ◽  
Thomas Zilli ◽  
Philippe Millet ◽  
Giovanni B. Frisoni ◽  
Valentina Garibotto ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
Animal Models ◽  
Phase Iii ◽  
Current Status ◽  
Central Feature ◽  
Phase Iii Trial ◽  
The Past ◽  
Positive Results

Alzheimer’s Disease (AD) is the most common neurodegenerative disease and cause of dementia. Characterized by amyloid plaques and neurofibrillary tangles of hyperphosphorylated Tau, AD pathology has been intensively studied during the last century. After a long series of failed trials of drugs targeting amyloid or Tau deposits, currently, hope lies in the positive results of one Phase III trial, highly debated, and on other ongoing trials. In parallel, some approaches target neuroinflammation, another central feature of AD. Therapeutic strategies are initially evaluated on animal models, in which the various drugs have shown effects on the target (decreasing amyloid, Tau and neuroinflammation) and sometimes on cognitive impairment. However, it is important to keep in mind that rodent models have a less complex brain than humans and that the pathology is generally not fully represented. Although they are indispensable tools in the drug discovery process, results obtained from animal models must be viewed with caution. In this review, we focus on the current status of disease-modifying therapies targeting amyloid, Tau and neuroinflammation with particular attention on the discrepancy between positive preclinical results on animal models and failures in clinical trials.

Clonal Markers In Relapsed Acute Promyelocytic Leukemia (APL): Clinicopathological Associations and Relation to All-Trans Retinoic Acid (ATRA) Treatment on Intergroup Phase III Trial C9710.

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 1038-1038
Author(s):  
Robert E. Gallagher ◽  
Barry K. Moser ◽  
Janis Racevskis ◽  
Xavier Poiré ◽  
Clara D. Bloomfield ◽  
...  
Keyword(s):  
Conflicts Of Interest ◽  
Cell Clone ◽  
Strong Association ◽  
False Negative ◽  
Phase Iii ◽  
Atra Treatment ◽  
Sensitivity Testing ◽  
Clinicopathologic Characteristics ◽  
Phase Iii Trial ◽  
Wbc Count

Abstract Abstract 1038 The relationships of inherent disease-related characteristics and of treatment to the nature of APL cell clones that emerge at disease relapse are poorly understood. We studied these relationships in 45 patients who relapsed after ATRA/chemotherapy treatment on the non-arsenic trixoxide arm of intergroup phase III trial C9710 (Powell, et al. Blood, Epub). Four variably-expressed APL cell clonal markers were assessed: PML-RARA ligand binding domain mutations (LBD-M), FLT3 internal tandem duplication mutations (ITD), FLT3 receptor tyrosine kinase mutations (D835; RTK-M) and additional chromosome abnormalities (ACA), i.e., in addition to the hallmark t(15;17). The methods for mutation analysis of PML-RARA and FLT3 have been reported and were RNA transcript-initiated supplemented by selected quantitative FLT3 mutation analyses initiated from DNA. Karyotype data were derived by standard cytogenetic methods. Four patients were excluded from analysis because the sample level of PML-RARA, as determined by quantitative RT-PCR, was insufficient to exclude possible false-negative mutation results. In 41 evaluable patients, the marker incidences were: LBD-M, 44%; ITD, 37%; RTK-M, 12%; ACA (22 tested), 59%. At presentation, the corresponding incidences were: LBD-M, 0% (by high-sensitivity testing a minor subclone of the relapse mutation was found in 2/7 patients tested); ITD, 43% (37 tested); RTK-M, 22% (37 tested); ACA, 24% (34 tested). The low frequency of RTK-M impeded further analysis. The other markers, using relapse determinations, were assessed for potential associations between the markers and with the following parameters: age, sex, presenting WBC count, PML-RARA type, time to relapse, relapse on or off ATRA treatment (on = taking or within 30 days of discontinuing) and post-relapse survival. The most essential positive findings are summarized below:Association of Marker with Parameter or Other MarkerCases with ParameterCases without Parameterp-valuePretreatment parameters:    LBD-M with WBC count < 5,000/uL12/18 (67%)7/23 (30%)0.030    ITD with WBC count >10,000/uL10/15 (67%)5/26 (19%)0.006    ITD with S-form PML-RARA15/15 (100%)10/26 (38%)<0.0001Relapse parameters:    ITD with lack of ACA1/7 (14%)12/15 (80%)0.007    LBD with relapse On-ATRA11/18 (61%)7/23 (30%)0.064    Off-ATRA only: LBD with lack of ITD0/7 (0%)9/16 (56%)0.019 The results confirm reports, which tested pretreatment samples, of a strong association between FLT3ITD mutations present at relapse and high WBC count and S-form PML-RARA. At relapse, there was, also, divergent selection of ITD-harboring vs ACA-harboring clones. LBD-M occurred more frequently in patients with low presenting WBC counts. They, also, occurred in patients who relapsed while on ATRA, consistent with an ATRA selective role for clones harboring LBD mutations. A significant segregation of patients with LBD-M or ITD was observed after relapse off ATRA treatment (p = 0.019), while no segregation was observed in overall relapse patients (p = 0.346) or after relapse on ATRA (p = 0.316). In 2 patients who relapsed on ATRA, quantitative analysis indicated that LBD-M and ITD mutations must be present in the same APL cell clone. There were no significant survival differences related to any clonal marker (post-relapse survival = 66%). Although the small number of cases is cautionary, the overall data suggest that LBD-M may have an overriding, dominant APL clone selection role in relapse that occurs on ATRA therapy. Other inherent clinicopathologic characteristics of APL may predispose to divergent molecular pathways of disease progression and relapse in patients alternatively harboring clones with LBD-M or ITD after the termination of ATRA selection pressure. Disclosures: No relevant conflicts of interest to declare.

Comparing Toxicities and Survival Outcomes with Total Therapy 4 (TT4) for 70-Gene (R70)-Defined Low-Risk Multiple Myeloma (MM) to Results Obtained with Total Therapy 3 Protocols TT3A and TT3B

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 368-368 ◽  
Author(s):  
Elias J. Anaissie ◽  
Frits van Rhee ◽  
Antje Hoering ◽  
Sarah Waheed ◽  
Yazan Alsayed ◽  
...  
Keyword(s):  
High Risk ◽  
Conflicts Of Interest ◽  
Low Risk ◽  
Phase Iii ◽  
Survival Outcomes ◽  
Phase Iii Trial ◽  
Baseline Characteristics ◽  
Total Therapy ◽  
Timing Of Onset

Abstract Abstract 368 Background: TT3, incorporating bortezomib and thalidomide with induction prior to and consolidation after melphalan 200mg/m2-based transplants and 3 year maintenance with VTD (year 1) and TD (years 2+3) in TT3A and with VRD for 3 years in TT3B resulted in a high CR rate of ∼60% and, in the 85% of patients with GEP-defined low-risk MM, 5-yr OS/EFS of 80%/78%; 5-year CR duration estimate was 88%. Patients and Methods: Phase III trial TT4 for low-risk MM randomized patients between standard (S) and light (L) arms. TT4-L applied 1 instead of 2 cycles of induction therapy with M-VTD-PACE prior to and 1 instead of 2 cycles of consolidation with dose-reduced VTD-PACE after tandem transplantation. M-VTD-PACE comprised melphalan, bortezomib, thalidomide, dexamethasone and 4-day continuous infusions of cisplatin, doxorubicin, cyclophosphamide, etoposide. TT4-S applied standard single dose melphalan 200mg/m2, while TT4-L used a 4-day fractionated schedule of melphalan 50mg/2 on days 1–4. VRD maintenance for 3 years was identical in both arms. Here we report, for both TT4 arms combined, on grade >2 mucosal toxicities, applying CTCAE version 3.0, and on efficacy (CR, EFS, OS) in relationship to TT3 in low-risk MM. At the time of analysis, median follow-up on TT4 is 10.7 months and on TT3A/B 62.3/33.4 months. To facilitate comparisons between trials with different follow-up times, TT3 data were backdated to follow-up time comparable to TT4 as of this reporting time. Results: Baseline characteristics were similar in TT3 (n=364) and TT4 (n=165) in terms of B2M both >=3.5mg/L and >5.5mg/L, and elevated levels of CRP, creatinine, and LDH. Presence of cytogenetic abnormalities (CA) overall and in terms of CA13/hypodiploidy was similar in both. Fewer TT4 patients had ISS-1 (31% v 43%, P=0.010) and more had hemoglobin <10g/dL (35% v 26%, P=0.029). While neither trial had GEP-defined high-risk in the 70-gene model (R70), the more recently validated R80 distribution showed 7% high-risk in TT4 v 3% in TT3 (P=0.031). DelTP53 was more prevalent in TT4 than TT3 (39% v 10%, P<0.001), and MY favorable subgroup designation pertained to 3% in TT4 v 12% in TT3 (P=0.002). Toxicities are reported per protocol phase. During induction (TT4, n=160; TT3, n=364), grade >2 mucosal toxicities included colitis in 0%/1% (P=0.32), esophagitis/dysphagia in 0%/1% (P=0.33), GI mucositis, NOS in 1%/1% (P=0.99) and stomatitis/pharyngitis in 0%/1% (P=0.99). With transplant-1, (TT4, n=139; TT3, n=344), grade >2 mucosal toxicities included colitis in 3%/1% (P=0.24), esophagitis/dysphagia in 1%/5% (P=0.03), gastritis in 1%/0% (P=0.29), GI mucositis, NOS in 1%/2% (P=0.73) and stomatitis/pharyngitis in 0%/5% (P=0.008); with transplant-2 (TT4, n=105; TT3, n=294), grade >2 mucosal toxicities included colitis in 4%/3% (P=0.77), esophagitis/dysphagia in 0%/2% (P=0.20), GI mucositis, NOS in 2%/3% (P=0.99) and stomatitis/pharyngitis in 0%/1% (P=0.58). With consolidation (TT4, n=85; TT3, n=280), grade >2 mucosal toxicities included colitis in 0%/3% (P=0.36) and GI mucositis, NOS in 0%/1% (P=0.99). Timing of onset and final levels of CR differed substantially between TT4 and TT3 in favor of TT4 (P=0.006); no differences were observed in OS (P=0.36), EFS (P=0.66), and CR duration (P=0.12). Conclusion: TT4 (both arms combined) provided, despite higher proportions of patients with unfavorable characteristics than in TT3, superior CR rate and comparable survival outcomes to TT3's low-risk population. GI toxicities were reduced in TT4 v TT3. Results of TT4 arms will be presented. Disclosures: No relevant conflicts of interest to declare.

Comparing the outcomes of noninferiority (NI) and superiority phase III trials.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. e13055-e13055
Author(s):  
Everardo D. Saad ◽  
Marc E. Buyse
Keyword(s):  
Progression Free Survival ◽  
Median Number ◽  
Phase Iii ◽  
Experimental Therapy ◽  
Tumor Type ◽  
Margin Width ◽  
Number Of Patients ◽  
Significant Difference ◽  
Phase Iii Trials ◽  
Superiority Trials

e13055 Background: We compared the outcomes of NI and superiority trials on advanced breast cancer (BC), non-small-cell lung cancer (NSCLC), and colorectal cancer (CRC). Methods: We searched PubMed for phase III trials on systemic antineoplastic treatments for advanced BC, NSCLC and CRC published between 1/1998 and 12/2009 in 11 leading journals. We categorized primary endpoints (PEP) as time-to-event (overall survival or any variant of progression-free survival), response rate, or other (quality of life or toxicity). We used the PEP (defined as the one stated explicitly, used for N calculation, or cited first) to ascertain trial positivity. Results: We retrieved a total of 262 trials (93 on BC, 102 on NSCLC, and 67 on CRC), 36 of which (13.7%) used a NI design (12 in each tumor type). There was no significant trend in the proportion of NI trials in the two 6-year periods compared (1998-2003 vs 2004-9). The median number of patients/arm for NI and superiority trials were 284 and 164, respectively (p<0.001). There was no significant difference in the distribution of the PEP categories between NI and superiority trials. We could ascertain trial positivity in all but six trials: 24 (66.7%, 95% confidence interval [CI], 49.1% to 81.2%) NI trials were positive, compared with 89 (39.4%, 95% CI, 33.0% to 46.1%) superiority trials (p<0.001). NI trial positivity could be determined by finding a CI for the estimated treatment effect that excluded the NI margin in 15 of 27 trials (otherwise, positivity was based on authors’ conclusions, or the experimental therapy was superior to control for the PEP). The overall rates of trial positivity varied across tumor types: 48.4% for BC, 31.4% for NSCLC, and 53.7% for CRC (p=0.002). When adjusted for trial size, NI design (vs. superiority; odds ratio [OR]=4.2; 95% CI, 1.7 to 10.3) and tumor type (BC [OR=2.2; 95% CI, 1.2 to 4.0] and CRC [OR=2.8; 95% CI, 1.4 to 5.5] vs. NSCLC as reference) remained significantly associated with trial positivity. Conclusions: NI trials are more likely than superiority trials to yield positive results. The influence of NI margin width on trial results should be investigated.

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