Wnt/β-catenin pathway alterations in non-small cell lung cancer (NSCLC) are associated with poor prognosis and resistance. In 598 stage III-IV NSCLC patients receiving platinum-based chemotherapy at MD Anderson Cancer Center (MDACC), we correlated survival with 441 host SNPs in 50 Wnt pathway genes. We then assessed the most significant SNPs in 240 Mayo Clinic patients receiving platinum-based chemotherapy for advanced NSCLC, 127 MDACC patients receiving platinum-based adjuvant chemotherapy and 340 early stage MDACC patients undergoing surgery alone (cohorts 2–4). In multivariate analysis, survival correlates with SNPs for AXIN2 (rs11868547 and rs4541111, of which rs11868547 was assessed in cohorts 2–4), Wnt-5B (rs12819505), CXXC4 (rs4413407) and WIF-1 (rs10878232). Median survival was 19.7, 15.6, and 10.7 months for patients with 1, 2, and 3–5 unfavorable genotypes, respectively (p= 3.8×10−9). Survival tree analysis classified patients into two groups (MST 11.3 vs 17.3 months, p=4.7×10−8). None of the SNPs achieved significance in cohorts 2–4; however, there was a trend in the same direction as cohort 1 for 3 of the SNPs. Using online databases, we found rs10878232 displayed expression quantitative trait loci (eQTL) correlation with the expression of LEMD3, a neighboring gene previously associated with NSCLC survival. In conclusion, results from cohort 1 provide further evidence for an important role for Wnt in NSCLC. Investigation of Wnt inhibitors in advanced NSCLC would be reasonable. Lack of a SNP association with outcome in cohorts 2–4 could be due to low statistical power, impact of patient heterogeneity, or false positive observations in cohort 1.

Randomized controlled trials with a survival endpoint are the gold standard for clinical research, but have failed to achieve cures for most advanced malignancies. The high costs of randomized clinical trials slow progress (thereby causing avoidable loss of life) and increase health care costs. A malignancy may be caused by several different mutations. Therapies effective vs one mutation may be discarded due to lack of statistical significance across the entire population. Conversely, expensive large randomized trials may have sufficient statistical power to demonstrate benefit despite the therapy only working in subgroups. Non-cost-effective therapy is then applied to all patients (including subgroups it cannot help). Randomized trials comparing therapies with different mechanisms of action are misleading since they may conclude the therapies are "equivalent" despite benefitting different subpopulations, or may erroneously conclude that one therapy is superior simply because it targets a larger subpopulation. Furthermore, minor variances in patient selection may determine study outcome, a therapy may be discarded as ineffective despite substantial benefit in one subpopulation if harmful in another, randomized trials may more effectively detect therapies with minor benefit in most patients vs marked benefit in subpopulations, and randomized trials in unselected patients may erroneously conclude that "shot-gun" combinations are superior to single agents when sequential administration of personalized single agents might work better and spare patients treatment with drugs that cannot help them. We must identify predictive biomarkers early by comparing responding to progressing patients in phase I-II trials. Enriching randomized trials for biomarker-positive patients can markedly reduce required patient numbers and costs despite expensive screening for biomarker-positive patients. Available data support approval of new drugs without randomized trials if they yield single-agent sustained responses in patients refractory to standard therapies. Conversely, new approaches are needed to guide development of drug combinations since both standard phase II approaches and phase II-III randomized trials have a high risk of misleading. Traditional randomized clinical trials approaches are often inefficient, wasteful, and unreliable. New clinical research paradigms are needed. The primary outcome of clinical research should be "Who (if anyone) benefits?" rather than "Does the overall group benefit?"

It takes on average 6–12 years to develop new anticancer drugs from discovery to approval. Effective new agents prolong survival. To demonstrate the importance of rapid drug approval, we calculated life‐years potentially saved if selected agents were approved more rapidly. As illustrative examples, we used 27 trials documenting improvements in survival. We multiplied improvement in median survival by numbers of patients dying annually and multiplied this by number of years from drug discovery until approval. For every year by which time to drug approval could have been shortened, there would have been a median number of life‐years potentially saved of 79,920 worldwide per drug. Median number of life‐years lost between time of drug discovery and approval was 1,020,900 per example. If we were able to use available opportunities to decrease the time required to take a drug from discovery to approval to 5 years, the median number of life‐years saved per example would have been 523,890 worldwide. Various publications have identified opportunities to speed drug development without sacrificing patient safety. While many investigational drugs prove to be ineffective, some significantly prolong survival and/or reduce suffering. These illustrative examples suggest that a substantial number of life‐years could potentially be saved by increasing the efficiency of development of new drugs for advanced malignancies.

Historically, subject matter experts and healthcare professionals have played a pivotal role in driving oncology clinical trials. Although patients have been key participants, their deliberate and active contribution to the design and decision-making process has been limited. This scoping review aimed to examine the existing literature to scope the extent of active patient engagement in the design of oncology clinical trials and its corresponding influence on trial outcomes. We conducted a systematic search using two databases, namely MEDLINE (Ovid) and EMBASE, to identify relevant studies exploring patient engagement in cancer-related clinical research design. We identified seven studies that met the eligibility criteria. The studies highlighted the benefits of active patient involvement, such as improved recruitment strategies, and the attainment of more patient-centered trial outcomes. The influence of patient involvement varied from tangible developments like patient-friendly resources to indirect impacts like improved patient experiences and potentially higher adherence to trial intervention. The future of clinical trials should prioritize patients’ values and perspectives, with regulatory bodies fostering these practices through clear guidelines. As the concept of patient centricity takes root in oncology research, the involvement of patients should evolve beyond mere participation.

High costs of complying with drug development regulations slow progress and contribute to high drug prices and, hence, mounting health care costs. If it is exorbitantly expensive to bring new therapies to approval, fewer agents can be developed with available resources, impeding the emergence of urgently needed treatments and escalating prices by limiting competition. Excessive regulation produces numerous speed bumps on the road to drug authorization. Although an explosion of knowledge could fuel rapid advances, progress has been slowed worldwide by inefficient regulatory and clinical research systems that limit access to therapies that prolong life and relieve suffering. We must replace current compliance-centered regulation (appropriate for nonlethal diseases like acne) with “progress-centered regulation” in lethal diseases, where the overarching objective must be rapid, inexpensive development of effective new therapies. We need to (i) reduce expensive, time-consuming preclinical toxicology and pharmacology assessments, which add little value; (ii) revamp the clinical trial approval process to make it fast and efficient; (iii) permit immediate multiple-site trial activation when an eligible patient is identified (“just-in-time” activation); (iv) reduce the requirement for excessive, low-value documentation; (v) replace this excessive documentation with sensible postmarketing surveillance; (vi) develop pragmatic investigator accreditation; (vii) where it is to the benefit of the patient, permit investigators latitude in deviating from protocols, without requiring approved amendments; (viii) confirm the value of predictive biomarkers before requiring the high costs of IDE/CLIA compliance; and (ix) approve agents based on high phase I–II response rates in defined subpopulations, rather than mandating expensive, time-consuming phase III trials. Clin Cancer Res; 21(20); 4561–8. ©2015 AACR. See all articles in this CCR Focus section, “Innovations to Speed Drug Development.”

Lung cancer is the world’s leading cause of cancer death,¹ x 1 Jemal, A, Bray, F, Center, MM, Ferlay, J, Ward, E, and Forman, D. Global cancer statistics. CA Cancer J Clin. 2011; 61: 69–90 Crossref | PubMed | Scopus (25119) | Google Scholar See all References and U.S. lung cancer 5-year relative survival rate has only increased from 12% in 1975–1977 to 16% currently.² x 2 Siegel, R, Naishadham, D, and Jemal, A. Cancer statistics, 2012. CA Cancer J Clin. 2012; 62: 10–29 Crossref | PubMed | Scopus (9344) | Google Scholar See all References The poor prognosis of lung cancer is due in part to a high proportion of patients presenting initially with advanced disease, but even patients with operable early-stage disease are at moderately high risk of relapse.³ x 3 Chansky, K, Sculier, JP, Crowley, JJ, Giroux, D, Van Meerbeeck, J, and Goldstraw, P. International Staging Committee and Participating Institutions. . The International Association for the Study of Lung Cancer Staging Project: prognostic factors and pathologic TNM stage in surgically managed non-small cell lung cancer. J Thorac Oncol. 2009; 4: 792–801 Abstract | Full Text | Full Text PDF | PubMed | Scopus (280) | Google Scholar See all References Adjuvant chemotherapy reduces the probability of relapse after lung cancer resection, but we are currently not able to accurately determine which patients actually need adjuvant therapy. In patients with resected stage I and II non–small-cell lung cancer (NSCLC), we assessed association with time to relapse (TTR) and overall survival (OS) of various tumor markers related to tumor growth rate, growth control, tumor cell survival and death, and hypoxia. In defining clinically important biomarkers to predict tumor biological behavior, OS is a more precise end point than TTR, but it has the major disadvantage that it is affected by several factors unrelated to tumor biology, including patient age, comorbidities, and therapy details.⁴ x 4 Stewart, DJ and Kurzrock, R. Fool's gold, lost treasures, and the randomized clinical trial. BMC Cancer. 2013; 13: 193 Crossref | PubMed | Scopus (29) | Google Scholar See all References Hence, our primary objective was to define factors associated with TTR (defined as the time from surgery to tumor recurrence, with patients censored at time of last follow-up (LFU), death from other causes, or development of a new primary malignancy [in lung or any other site] that was associated with metastases, if they remained free of evidence of recurrence of their initial primary lung cancer at that time).