Reporting of Health-Related Quality of Life Outcome Measures in Genotype based Targeted Therapies for Advanced Cancers

Reporting of Health-Related Quality of Life Outcome Measures in Genotype based Targeted Therapies for Advanced Cancers | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Reporting of Health-Related Quality of Life Outcome Measures in Genotype based Targeted Therapies for Advanced Cancers Tik Fung Dave Liu, Farasat Kazmi, Caroline Barry, Shiva Raj Mishra, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7091849/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Background Genotype based matched targeted therapies (MTT) trials have shown clinical benefit in patients with advanced cancer however health-related quality of life (HRQoL) outcomes are often inconsistently reported in these trials. In this study, we evaluated the overall reporting and quality of HRQoL based randomised controlled trials (RCTs). Methods We searched various biomedical databases (CENTRAL, MEDLINE, EMBASE) from 2000 to 2024, for eligible RCTs evaluating biomarker based MTTs (alone or combined with standard of care systemic standard-of-care [SOC]) versus SOC or placebo in patients with advanced cancers that had progressed after at least one prior systemic therapy. We evaluated inclusion of HRQoL endpoints, timing of reporting, tools used, and adherence to selected CONSORT-PRO guidelines. Results A total of 208 studies were assessed for eligibility. No studies reported HRQoL as a primary endpoint. Among 61 RCTs (n = 21,103), HRQoL was included as a secondary or exploratory endpoint in 35 (57.4%) trials. Only 17 (27.9%) trials reported HRQoL in the primary publication. Inclusion and reporting declined over time, with only 44.0% of trials after 2020 including HRQoL and just 8.0% reporting it in the primary publication. Trials with positive primary outcomes reported HRQoL more frequently and earlier. Compliance with CONSORT-PRO was poor: no trial stated HRQoL in their hypothesis or described handling of missing data. Common instruments included EORTC QLQ (n = 20), FACT (n = 14), and EQ-5D (n = 10). Conclusion HRQoL is significantly under-reported in MTT based trials, with declining inclusion and poor adherence to reporting standards. This is particularly important as MTT do not significantly improve overall survival in this cohort and therefore quality of life becomes paramount for these patients. Quality of life matched targeted therapies advanced cancer Figures Figure 1 1. BACKGROUND Matched targeted therapies (MTTs) have become a cornerstone of personalised cancer treatment, particularly for patients with advanced or refractory malignancies ( 1 ). These therapies, which are selected based on tumour-specific genetic or molecular alterations, have demonstrated improved progression free survival either as monotherapy or in combination with standard systemic anticancer treatments, however there is limited improvement in overall survival ( 2 , 3 ). A recent Cochrane meta-analysis highlighted the lack of evidence on the impact of MTTs on quality of life in patients with advanced cancers ( 2 ). This gap is concerning, patient reported outcomes (PROs) such as health related quality of life (HRQoL) are increasingly recognized as a critical outcome in oncology, particularly in non-curative settings where prolongation of life may be modest, and the interventions that improve physical and psychological wellbeing may be of more important ( 4 ). Health-related quality of life are questionnaires completed by patients that encompasses multiple domains of patient perspective on his/her health. The domains in these questionnaires frequently include physical functioning, emotional health, symptom burden, and social participation—and provides insight into how a treatment affects patients beyond traditional clinical safety and efficacy. HRQOL can play a pivotal role in shared treatment decision-making and are increasingly recognized as critical outcomes for guiding clinical recommendations and shaping health policy ( 5 ). Despite this, HRQoL assessments are inconsistently implemented and reported in clinical trials ( 5 ). In some cases, they are omitted entirely, particularly when treatments are anticipated to have higher adverse events ( 6 , 7 ). This selective and inconsistent reporting raises concerns about bias and underscores the need for standardized, transparent, and patient-centered reporting practices ( 8 ). To improve the quality and transparency of HRQoL reporting, the CONSORT-PRO (Consolidated Standards of Reporting Trials–Patient-Reported Outcomes) extension was introduced in 2013 ( 9 , 10 ). The guideline outlined a set of recommendations designed to ensure the completeness, consistency, and interpretability of patient-reported outcome data in randomized trials ( 10 ). Despite this, HRQoL data collection is still inconsistently reported ( 5 ). In addition, variability in measurement tools, and delays in publication of patient-reported outcomes further limit the interpretability and clinical relevance of HRQoL outcomes ( 9 , 11 ). In this study, we aim to systematically review these concerns in targeted therapy trials for pretreated metastatic or relapsed cancer by evaluating their inclusion, reporting, and quality of HRQoL data. 2. METHODS Eligibility criteria and Literature search We conducted a comprehensive search in three databases namely CENTRAL, EMBASE and MEDLINE without language restrictions until 30th October 2024 (Supplementary 1). Additionally, we checked reference lists of included studies, previous systematic reviews, and studies citing eligible articles. The 'related articles' feature in PubMed was also utilized. Furthermore, conference reports from the past five years were sourced from the following meetings: European Haematology Association, American Society of Haematology, European Society of Medical Oncology (ESMO), American Society of Clinical Oncology (ASCO) and British Cancer Research Meeting. Studies comparing MTT alone or in combination with standard-of-care treatment, either chemotherapy or hormonal therapy, were considered. Only randomized controlled trials were included. Studies comparing MTT with immunotherapy or immune modulators were excluded to maintain consistency with our previously published systematic review ( 2 ). Selection of studies Titles and abstracts retrieved from the database searches were screened in duplicate. Studies selected for full-text screening were also assessed in duplicate. Disagreements were resolved through consensus. In instances where HRQoL results were not reported in the primary publication, a secondary search was conducted to identify companion publications reporting HRQoL data. These secondary publications were identified via PubMed and google using the name of the drug, the trial registration number and trial acronym. Data Extraction Data was extracted by a study author (TF) and rechecked by a second a second author (NS). Any discrepancy identified in the extraction was resolved by consensus. For each included RCT, data were extracted from the primary and secondary publications, associated supplementary materials, and the ClinicalTrials.gov registry. Extracted trial characteristics included: first author, study acronym, year of publication, digital object identifier (DOI), journal name, type of therapy and intervention, tumour type, primary endpoint, trial design (classified as superiority or non-inferiority), blinding (blinded or open-label), comparator type (placebo or other), trial outcome (classified as positive or negative based on the statistical significance of the primary endpoint), funding source (pharmaceutical industry sponsored vs. non-profit or academic), and geographical scope (single-country or multi-country trial conduct). To assess the reporting of HRQoL outcomes, main manuscripts and study protocols/trial registry records were reviewed to determine whether HRQoL was included as a trial endpoint. For each publication that included HRQoL as their endpoints, the following additional information was extracted: whether HRQoL data was reported in the primary or secondary publication, the time elapsed between primary and secondary publication (in days and months), the type of assessment tools used and reported compliance with HRQoL questionnaires. Statistical analysis and Adherence to CONSORT PRO checklist All statistical analyses were conducted using R version 4.1.2 (R Foundation for Statistical Computing, Vienna, Austria). Differences in the reporting of health-related quality of life (HRQoL) as a primary, secondary, or exploratory endpoint were examined. The reporting of HRQoL in primary and subsequent trial publications was also assessed. Kaplan–Meier survival curves were generated to estimate the time to HRQoL data publication. For trials published from 2013 onwards, adherence to the CONSORT-PRO extension for reporting patient-reported outcomes (PROs) was evaluated using selected checklist items, as outlined at http://www.consort-statement.org/extensions . 3. RESULTS 3.1 Study selection A total of 208 full-text articles were screened for full-text assessment. Of these, 147 studies were excluded for reasons: absence of a comparator arm (n = 46), use of the wrong line of treatment (n = 28), inappropriate study design (n = 18), retrospective cohort design (n = 15), wrong intervention (n = 8), wrong patient population (n = 7), ongoing trial status (n = 7), wrong setting (n = 5), wrong outcomes (n = 4), wrong comparator (n = 4), prospective cohort study design (n = 4), or lack of full publication of data (n = 1). This resulted in a final inclusion of 61 randomized controlled trials (RCTs) for this analysis. The study selection process is summarized in Fig. 1 . 3.2 Study characteristics A total of 61 eligible RCTs ( 12 – 72 ) were published between 2008 and 2024. Of these, 25 (41%) trials were published after 2020, followed by 31 (51%) trials published between 2011–2020. Based on tumour sites, 22 (36%) trials were related to breast and prostate cancer studies, followed by 14 (23%) studies in lung and gynaecological cancers. Detailed study characteristics can be found in Table 1 . 3.3 Primary Endpoints and Inclusion of HRQoL in Trial Designs Progression-free survival (PFS) and overall survival (OS) were the most reported primary endpoints, included in 44 (72%) and 9 (14%) studies respectively (Table 1 ). Overall response rate (ORR) and other endpoints were reported in 5 (8%) and 3 (5%) trials respectively. Notably, none of the 61 trials included HRQoL as a primary endpoint. HRQoL was included as a secondary endpoint in 26 trials (43%) and as an exploratory endpoint in 9 trials (15%), while it was not evaluated in 26 trials (43%) (Table 1 ). Among the 49 positive trials, HRQoL was not assessed in 19 (39%), whereas among the 12 negative trials, 7 (58%) did not include HRQoL assessment. HRQoL was more frequently evaluated in certain tumour types, such as gynaecological cancers (86%) and lung cancer (57%). Only half of breast cancer trials reported HRQoL endpoints. Among the 35 trials that included HRQoL as a secondary or exploratory endpoint, many employed more than one assessment instrument. Therefore, the total number of tool usages exceeds the number of trials. The most frequently used instrument was the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ), which appeared in 20 instances. This was followed by the Functional Assessment of Cancer Therapy (FACT) family of tools (n = 14) and the EQ-5D-5L (n = 10). Other tools included the Brief Pain Inventory (BPI; n = 5) and a small number of trial-specific or less commonly used instruments. A detailed description of HRQoL inclusion by trial characteristics is reported in Table 1 . Table 1. Study Characteristics and HRQoL Inclusion as Secondary or Exploratory Endpoints. Other Cancers Head and Neck, Upper GI, Skin, Bladder. Abbreviations: ORR: objective response rate, OS: overall survival, PFS: progression free survival, EORTC QLQ: European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire, FACT: Functional Assessment of Cancer Therapy, EQ-5D-5L: EuroQol 5-Dimension 5-Level Questionnaire, BPI: brief pain inventory, NFOSI: NCCN–Functional Assessment of Cancer Therapy Ovarian Symptom Index, PGI: patient global impression, TOI: trial outcome index 3.4 Reporting of HRQoL Results in Primary Publications We assessed whether HRQoL results were reported in the primary publication. Among the 61 included RCTs, only 17 (28%) reported HRQoL outcomes in their main manuscript, while the remaining 44 (72%) did not (Table 2 ). A notable trend emerged over time, with HRQoL reporting becoming less common in more recent trials. Among studies published after 2020, only 2 out of 25 (8%) reported HRQoL results in the primary publication, compared to 11 out of 23 (48%) for trials published between 2016 and 2020. Regarding trial results, HRQoL outcomes were reported in 16 out of 49 positive trials (33%) and only 1 out of 12 negative trials (8%). When examined by tumour type, HRQoL reporting was most frequent in trials on lung cancer (57%). Finally, among the 9 trials with missing data on HRQoL compliance rates, 7 (66.7%) reported HRQoL in the primary publication, while 2 (33.3%) did not. A complete breakdown of HRQoL reporting across study characteristics is presented in Table 2 . Table 2. Study Characteristics and Inclusion of HRQoL in Primary Publication Other Cancers Head and Neck, Upper GI, Skin, Bladder. Abbreviations: ORR: objective response rate, OS: overall survival, PFS: progression free survival 3.5 Compliance with CONSORT PRO reporting standards Among the trials that reported their HRQoL results, we evaluated compliance with selected items from the CONSORT-PRO extension checklist among trials that reported HRQoL in either the primary or a secondary publication and were published from 2013 onward. A total of 26 trials met these criteria and were included in this analysis. Identification of the patient-reported outcome (PRO) as a primary or secondary endpoint in the abstract was fulfilled in only 6 trials (23%). None of the trials stated a PRO hypothesis or identified the relevant domains of interest, nor did any provide scientific background or rationale for PRO assessment. Information on the validity and reliability of the HRQoL instruments used was provided or cited in 19 trials (73%), representing the most consistently reported item. In contrast, statistical methods for handling missing PRO data were described in only 3 trials (12%). Transparency regarding the number of PRO outcome data at baseline and subsequent time points was reported in 17 trials (65.4%). Similarly, 17 trials (65.4%) presented results for each group along with estimated effect sizes and their precision. Fifteen trials (57.7%) included a table of baseline demographic and clinical characteristics. Only 2 trials (8%) discussed PRO-specific limitations or the implications of HRQoL findings for generalisability or clinical practice. No trials provided an interpretation that balanced benefits and harms while considering other relevant evidence. Full results of the CONSORT-PRO compliance analysis are presented in Table 3 and Supplementary Table 1. Table 3 CONSORT-PRO Checklist Compliance Among Trials Reporting HRQoL Checklist items n % RCTs reporting QoL in primary, secondary publication or both from 2013 *26 100 1b: The PRO should be identified in the abstract as a primary or secondary outcome 6 23 2a CONSORT 2010: Scientific background and explanation of rationale. 0 0 2b: The PRO hypothesis should be stated, and relevant domains identified, if applicable 0 0 6a: Evidence of PRO instrument validity and reliability should be provided or cited 19 73 12a: Statistical approaches for dealing with missing data are explicitly stated 3 11 13a CONSORT 2010: For each group, the numbers of participants who were randomly assigned, received intended treatment, and were analyzed for the primary outcome. 17 65 15 CONSORT 2010: A table showing baseline demographic and clinical characteristics for each group. 15 58 17a CONSORT 2010: For each primary and secondary outcome, results for each group, and the estimated effect size and its precision (such as 95% confidence interval). 17 65 20/21: PRO-specific limitations and implications for generalizability 2 8 22 CONSORT 2010: Interpretation consistent with results, balancing benefits and harms, and considering other relevant evidence. 0 0 *17 RCTs reported HRQoL data in their primary publication, 9 RCTs reported HRQoL data in their secondary publications 4. DISCUSSION Health-related quality of life remains under-prioritised and inconsistently reported in randomised controlled trials of matched targeted therapies for pretreated advanced cancers. Our findings are consistent with those of similar studies conducted in other cancer settings (Supplementary table 2). Despite the increasing use of biomarker-driven therapies in non-curative cancer settings, none of the 61 trials included HRQoL as a primary endpoint, and fewer than one in three reported HRQoL in the main publication. This is concerning, as the population under study often experiences marginal survival benefit, making patient-reported outcomes such as HRQoL especially vital for shared decision-making and patient-centred care ( 2 , 73 ). Our findings are consistent with similar studies, which have shown that improvements in PFS are poorly correlated with overall quality of life and do not reliably predict HRQoL benefit ( 6 , 7 ). Importantly, we found that trials showing PFS gains without HRQoL improvement often framed outcomes positively (e.g., "HRQoL maintained"), suggesting the presence of reporting bias (Supplementary table 1 ; ( 5 – 7 , 73 – 79 )). Furthermore, our CONSORT-PRO compliance analysis found no trials stating a prior HRQoL hypotheses, and few that described handling of missing data—both critical elements for methodological robustness (Table 3 and Supplementary Table 1). This further validates a consistent theme that most phase 3 trials fail to adjust HRQoL outcomes for baseline scores, introducing potential bias and reducing analytic validity ( 7 ). One particularly important insight from our review is the disparity in HRQoL reporting based on trial outcome. Trials with negative or non-significant results were significantly less likely to publish HRQoL data or do so in a timely fashion (Supplementary Figs. 1 and 2). These reporting delays critically hampers the ability of clinicians and policymakers to make informed evaluations about therapeutic value of MTTs, where toxicities may be chronic and insidious, and quality of life—not just tumour control—should drive clinical decision-making. For example, in a meta-analysis of 791 phase 3 oncology trials, they found that although 61% collected patient reported outcomes, only 34% published global HRQoL outcomes, and just 11% demonstrated global HRQoL superiority ( 7 ). It is also worth highlighting that HRQoL deterioration is more commonly associated with targeted agents than traditionally perceived ( 6 , 80 ). Samuel et al. noted that inferior HRQoL was more frequently observed with MTTs than with cytotoxic chemotherapy, challenging the assumption that "targeted" equates to "better tolerated" ( 6 ). Our own review supports this, with multiple trials using MTTs reporting PRO data that, when available, revealed significant symptom burden, yet without the necessary methodological clarity to interpret the data effectively. The strength of this study is that it specifically focusses on HRQoL outcomes in genotype based MTT trials for previously treated advanced cancer patients providing a better understanding the impact of MTT in this setting. However, there exist several limitations. First, despite a comprehensive search strategy, some eligible trials may have been missed. Second although we focused on published data, delayed or unpublished HRQoL results—particularly in negative trials—may have led to underestimation of the true reporting gap. Finally, the modest number of trials relative to broader reviews limits generalisability but enhances the specificity to MTTs, where these gaps are particularly concerning. 5. CONCLUSIONS In conclusion, the consistent under-reporting, delayed publication, and poor methodological quality of HRQoL data in MTT trials represents a major disconnect between precision oncology and patient-centred care. The emphasis on alternative endpoints such as PFS has overshadowed meaningful outcomes such as overall survival and quality of life. Therefore, Incorporating HRQoL as a core outcome from the outset of trial design—and reporting it transparently regardless of outcome—must become standard practice. Doing so will ensure treatments are evaluated not only by how long patients live, but also by how well they live. Abbreviations MTT: Matched targeted therapy SOC: Standard-of-care HRQoL: Health-related quality of life ORR: Objective response rate OS: Overall survival PFS: Progression free survival EORTC QLQ: European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire FACT: Functional Assessment of Cancer Therapy EQ-5D-5L: EuroQol 5-Dimension 5-Level Questionnaire BPI: brief pain inventory NFOSI: NCCN–Functional Assessment of Cancer Therapy Ovarian Symptom Index PGI: patient global impression TOI: trial outcome index Declarations Ethics approval and consent to participate: Not applicable Consent for publication: Not applicable Availability of data and materials : All data generated or analysed during this study are included in this published article [and its supplementary information files]. Competing interest: Authors declare no competing interest in preparing this manuscript. Author contributions: Conceptualization, methodology, formal analysis and investigation and writing original draft preparation: TF, FK, NS; Supervision: NS; Writing - review and editing: CB, SRM, PD, RK. All authors read and approved the final manuscript. Funding: No funding was received in preparing this manuscript. Acknowledgement: Not applicable References Min HY, Lee HY. Molecular targeted therapy for anticancer treatment. Exp Mol Med. 2022;54(10):1670-94. Kazmi F, Shrestha N, Liu TFD, Foord T, Heesen P, Booth S, et al. Next-generation sequencing for guiding matched targeted therapies in people with relapsed or metastatic cancer. Cochrane Database Syst Rev. 2025;3(3):CD014872. Yang TK, Yu YF, Tsai CL, Li HJ, Yang PS, Huang KW, Cheng JC. Efficacy and safety of combined targeted therapy and immunotherapy versus targeted monotherapy in unresectable hepatocellular carcinoma: a systematic review and meta-analysis. BMC Cancer. 2022;22(1):1085. 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TBCRC 032 IB/II Multicenter Study: Molecular Insights to AR Antagonist and PI3K Inhibitor Efficacy in Patients with AR(+) Metastatic Triple-Negative Breast Cancer. Clin Cancer Res. 2020;26(9):2111-23. Litton JK, Rugo HS, Ettl J, Hurvitz SA, Goncalves A, Lee KH, et al. Talazoparib in Patients with Advanced Breast Cancer and a Germline BRCA Mutation. N Engl J Med. 2018;379(8):753-63. Liu JF, Brady MF, Matulonis UA, Miller A, Kohn EC, Swisher EM, et al. Olaparib With or Without Cediranib Versus Platinum-Based Chemotherapy in Recurrent Platinum-Sensitive Ovarian Cancer (NRG-GY004): A Randomized, Open-Label, Phase III Trial. J Clin Oncol. 2022;40(19):2138-47. Loriot Y, Matsubara N, Park SH, Huddart RA, Burgess EF, Houede N, et al. Erdafitinib or Chemotherapy in Advanced or Metastatic Urothelial Carcinoma. N Engl J Med. 2023;389(21):1961-71. Mok TS, Wu YL, Ahn MJ, Garassino MC, Kim HR, Ramalingam SS, et al. Osimertinib or Platinum-Pemetrexed in EGFR T790M-Positive Lung Cancer. N Engl J Med. 2017;376(7):629-40. Peeters M, Price TJ, Cervantes A, Sobrero AF, Ducreux M, Hotko Y, et al. Randomized phase III study of panitumumab with fluorouracil, leucovorin, and irinotecan (FOLFIRI) compared with FOLFIRI alone as second-line treatment in patients with metastatic colorectal cancer. J Clin Oncol. 2010;28(31):4706-13. Penson RT, Valencia RV, Cibula D, Colombo N, Leath CA, 3rd, Bidzinski M, et al. Olaparib Versus Nonplatinum Chemotherapy in Patients With Platinum-Sensitive Relapsed Ovarian Cancer and a Germline BRCA1/2 Mutation (SOLO3): A Randomized Phase III Trial. J Clin Oncol. 2020;38(11):1164-74. Perl AE, Martinelli G, Cortes JE, Neubauer A, Berman E, Paolini S, et al. Gilteritinib or Chemotherapy for Relapsed or Refractory FLT3-Mutated AML. N Engl J Med. 2019;381(18):1728-40. Robson M, Im SA, Senkus E, Xu B, Domchek SM, Masuda N, et al. Olaparib for Metastatic Breast Cancer in Patients with a Germline BRCA Mutation. N Engl J Med. 2017;377(6):523-33. Rodler E, Sharma P, Barlow WE, Gralow JR, Puhalla SL, Anders CK, et al. Cisplatin with veliparib or placebo in metastatic triple-negative breast cancer and BRCA mutation-associated breast cancer (S1416): a randomised, double-blind, placebo-controlled, phase 2 trial. Lancet Oncol. 2023;24(2):162-74. Schlumberger M, Elisei R, Muller S, Schoffski P, Brose M, Shah M, et al. Overall survival analysis of EXAM, a phase III trial of cabozantinib in patients with radiographically progressive medullary thyroid carcinoma. Ann Oncol. 2017;28(11):2813-9. Soulieres D, Licitra L, Mesia R, Remenar E, Li SH, Karpenko A, et al. Molecular Alterations and Buparlisib Efficacy in Patients with Squamous Cell Carcinoma of the Head and Neck: Biomarker Analysis from BERIL-1. Clin Cancer Res. 2018;24(11):2505-16. Turner NC, Oliveira M, Howell SJ, Dalenc F, Cortes J, Gomez Moreno HL, et al. Capivasertib in Hormone Receptor-Positive Advanced Breast Cancer. N Engl J Med. 2023;388(22):2058-70. Wang J, Jiang B, Li J, Liu L, Du X, Jiang H, et al. Gilteritinib Versus Salvage Chemotherapy for Relapsed/Refractory FLT3-Mutated Acute Myeloid Leukemia: A Phase 3, Randomized, Multicenter, Open-Label Trial in Asia. Blood. 2021;138(Supplement 1):695-. Modi S, Jacot W, Yamashita T, Sohn J, Vidal M, Tokunaga E, et al. Trastuzumab Deruxtecan in Previously Treated HER2-Low Advanced Breast Cancer. N Engl J Med. 2022;387(1):9-20. Papadimitrakopoulou V, Lee JJ, Wistuba, II, Tsao AS, Fossella FV, Kalhor N, et al. The BATTLE-2 Study: A Biomarker-Integrated Targeted Therapy Study in Previously Treated Patients With Advanced Non-Small-Cell Lung Cancer. J Clin Oncol. 2016;34(30):3638-47. Rescigno P, Porta N, Finneran L, Riisnaes R, Figueiredo I, Carreira S, et al. Capivasertib in combination with enzalutamide for metastatic castration resistant prostate cancer after docetaxel and abiraterone: Results from the randomized phase II RE-AKT trial. Eur J Cancer. 2024;205:114103. Bang YJ, Xu RH, Chin K, Lee KW, Park SH, Rha SY, et al. Olaparib in combination with paclitaxel in patients with advanced gastric cancer who have progressed following first-line therapy (GOLD): a double-blind, randomised, placebo-controlled, phase 3 trial. Lancet Oncol. 2017;18(12):1637-51. Ciuleanu T, Stelmakh L, Cicenas S, Miliauskas S, Grigorescu AC, Hillenbach C, et al. Efficacy and safety of erlotinib versus chemotherapy in second-line treatment of patients with advanced, non-small-cell lung cancer with poor prognosis (TITAN): a randomised multicentre, open-label, phase 3 study. Lancet Oncol. 2012;13(3):300-8. Schlumberger M, Tahara M, Wirth LJ, Robinson B, Brose MS, Elisei R, et al. Lenvatinib versus placebo in radioiodine-refractory thyroid cancer. N Engl J Med. 2015;372(7):621-30. Soria JC, Wu YL, Nakagawa K, Kim SW, Yang JJ, Ahn MJ, et al. Gefitinib plus chemotherapy versus placebo plus chemotherapy in EGFR-mutation-positive non-small-cell lung cancer after progression on first-line gefitinib (IMPRESS): a phase 3 randomised trial. Lancet Oncol. 2015;16(8):990-8. Cortés J, Bidard FC, Bardia A, Kaklamani VG, Vlachaki I, Tonini G, et al. 188O EMERALD trial analysis of patient-reported outcomes (PROs) in patients with ER+/HER2− advanced or metastatic breast cancer (mBC) comparing oral elacestrant vs standard of care (SoC) endocrine therapy. ESMO Open. 2023;8(1). Brose MS, Robinson BG, Sherman SI, Jarzab B, Lin CC, Vaisman F, et al. Cabozantinib for previously treated radioiodine-refractory differentiated thyroid cancer: Updated results from the phase 3 COSMIC-311 trial. Cancer. 2022;128(24):4203-12. Dash AB, Zhang J, Shen L, Li B, Berg D, Lin J, et al. Clinical benefit of ixazomib plus lenalidomide-dexamethasone in myeloma patients with non-canonical NF-kappaB pathway activation. Eur J Haematol. 2020;105(3):274-85. Grob JJ, Amonkar MM, Karaszewska B, Schachter J, Dummer R, Mackiewicz A, et al. Comparison of dabrafenib and trametinib combination therapy with vemurafenib monotherapy on health-related quality of life in patients with unresectable or metastatic cutaneous BRAF Val600-mutation-positive melanoma (COMBI-v): results of a phase 3, open-label, randomised trial. Lancet Oncol. 2015;16(13):1389-98. Bardia A, Su F, Solovieff N, Im SA, Sohn J, Lee KS, et al. Genomic Profiling of Premenopausal HR+ and HER2- Metastatic Breast Cancer by Circulating Tumor DNA and Association of Genetic Alterations With Therapeutic Response to Endocrine Therapy and Ribociclib. JCO Precis Oncol. 2021;5. Brugger W, Triller N, Blasinska-Morawiec M, Curescu S, Sakalauskas R, Manikhas GM, et al. Prospective molecular marker analyses of EGFR and KRAS from a randomized, placebo-controlled study of erlotinib maintenance therapy in advanced non-small-cell lung cancer. J Clin Oncol. 2011;29(31):4113-20. Kim TW, Taieb J, Gurary EB, Lerman N, Cui K, Yoshino T. Olaparib with or without bevacizumab or bevacizumab and 5-fluorouracil in advanced colorectal cancer: Phase III LYNK-003. Future Oncol. 2021;17(36):5013-22. Noguchi E, Yamanaka T, Mukai H, Yamamoto N, Chung CF, Lu YS, et al. A phase 3 study (PATHWAY) of palbociclib plus tamoxifen in patients with HR-positive/HER2-negative advanced breast cancer. NPJ Breast Cancer. 2024;10(1):76. Reckamp KL, Koczywas M, Cristea MC, Dowell JE, Wang HJ, Gardner BK, et al. Randomized phase 2 trial of erlotinib in combination with high-dose celecoxib or placebo in patients with advanced non-small cell lung cancer. Cancer. 2015;121(18):3298-306. Hwang TJ, Gyawali B. Association between progression-free survival and patients' quality of life in cancer clinical trials. Int J Cancer. 2019;144(7):1746-51. Di Costanzo F, Napolitano F, Salomone F, Amato AR, Alberico G, Migliaccio F, et al. Analysis of Health-Related Quality of Life Reporting in Phase III RCTs of Advanced Genitourinary Tumors. Cancers (Basel). 2023;15(23). Marandino L, La Salvia A, Sonetto C, De Luca E, Pignataro D, Zichi C, et al. Deficiencies in health-related quality-of-life assessment and reporting: a systematic review of oncology randomized phase III trials published between 2012 and 2016. Ann Oncol. 2018;29(12):2288-95. Salomone F, Di Costanzo F, Pecoraro G, Viscardi G, Viggiano A, Napolitano F, et al. Health-related quality of life is underestimated and underreported in phase III clinical trials in NSCLC. Lung Cancer. 2022;174:36-44. Servetto A, Salomone F, Di Costanzo F, Iuliano R, Marandino L, Napolitano F, et al. Inadequate health-related quality of life assessment and reporting in phase III clinical trials of immune checkpoint inhibitors in solid cancers: A systematic review. Crit Rev Oncol Hematol. 2022;172:103649. St Germain D, Denicoff A, Torres A, Kelaghan J, McCaskill-Stevens W, Mishkin G, et al. Reporting of health-related quality of life endpoints in National Cancer Institute-supported cancer treatment trials. Cancer. 2020;126(11):2687-93. Waisberg F, Lopez C, Enrico D, Rodriguez A, Hirsch I, Burton J, et al. Assessing the methodological quality of quality-of-life analyses in first-line non-small cell lung cancer trials: A systematic review. Crit Rev Oncol Hematol. 2022;176:103747. Di Maio M, Basch E, Bryce J, Perrone F. Patient-reported outcomes in the evaluation of toxicity of anticancer treatments. Nat Rev Clin Oncol. 2016;13(5):319-25. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFileQolintargetedtherapytrialsDL.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 12 Jan, 2026 Reviews received at journal 07 Jan, 2026 Reviews received at journal 07 Jan, 2026 Reviewers agreed at journal 09 Nov, 2025 Reviewers agreed at journal 08 Nov, 2025 Reviewers agreed at journal 23 Aug, 2025 Reviews received at journal 22 Aug, 2025 Reviewers agreed at journal 21 Aug, 2025 Reviewers invited by journal 28 Jul, 2025 Editor assigned by journal 13 Jul, 2025 Submission checks completed at journal 13 Jul, 2025 First submitted to journal 10 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7091849","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":491756326,"identity":"3ccb894c-b61c-4d96-8c5e-4f23b83fe7a3","order_by":0,"name":"Tik Fung Dave Liu","email":"","orcid":"","institution":"Maidstone and Tunbridge Wells NHS Trust","correspondingAuthor":false,"prefix":"","firstName":"Tik","middleName":"Fung Dave","lastName":"Liu","suffix":""},{"id":491756327,"identity":"e574e706-6f24-4140-aeba-ddbd90ddc4a4","order_by":1,"name":"Farasat Kazmi","email":"","orcid":"","institution":"Norfolk and Norwich University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Farasat","middleName":"","lastName":"Kazmi","suffix":""},{"id":491756328,"identity":"09671288-d04c-404e-987c-deebbb214f4e","order_by":2,"name":"Caroline Barry","email":"","orcid":"","institution":"Norfolk and Norwich University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Caroline","middleName":"","lastName":"Barry","suffix":""},{"id":491756329,"identity":"e8f7a5b7-b0e2-405c-8302-bd1188fee387","order_by":3,"name":"Shiva Raj Mishra","email":"","orcid":"","institution":"Western Sydney University","correspondingAuthor":false,"prefix":"","firstName":"Shiva","middleName":"Raj","lastName":"Mishra","suffix":""},{"id":491756331,"identity":"35c70f8b-0bfc-4ff8-8173-474783ffe4a1","order_by":4,"name":"Padam Dahal","email":"","orcid":"","institution":"Royal Australasian College of Surgeons","correspondingAuthor":false,"prefix":"","firstName":"Padam","middleName":"","lastName":"Dahal","suffix":""},{"id":491756332,"identity":"2ec8c590-1f6b-43b5-a20b-ec0dc2ea2225","order_by":5,"name":"Raunica Katyal","email":"","orcid":"","institution":"Norfolk and Norwich University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Raunica","middleName":"","lastName":"Katyal","suffix":""},{"id":491756333,"identity":"54f66e6b-3bad-4f4f-a67e-4ea0446b0361","order_by":6,"name":"Nipun Shrestha","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYDCCA2AEBBLMIFpChngtPBJsCSAtPERpYYBo4TEA0wR18N0+e/BwYdsde3vpns+vbtRY8DCwHz66AZ8WyXN5CYdntj1L7JE5u8065xjQYTxpaTfwaTE4w2NwmLftcAKPRO424xw2oBYJHjOitNjzSOQ8M875R4IWxh6JHObHuW1EaJEEaZlx7nBiz400M+bcPgkeNkJ+4TvDY/y5oOywPfuM5Mefc77VyfGzHz6GVwsIMENpNgkwSUg5shbmD8SoHgWjYBSMgpEHAIbTSDuGhXNIAAAAAElFTkSuQmCC","orcid":"","institution":"The University of Adelaide","correspondingAuthor":true,"prefix":"","firstName":"Nipun","middleName":"","lastName":"Shrestha","suffix":""}],"badges":[],"createdAt":"2025-07-10 10:23:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7091849/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7091849/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88000336,"identity":"70e44b9f-170f-4744-bcdf-13681c2036e5","added_by":"auto","created_at":"2025-07-31 10:19:39","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":79683,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow diagram of study selection\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7091849/v1/12aad7b801134fcf92d44f1d.jpg"},{"id":88005527,"identity":"9ebb31a4-353d-4078-bd30-fa78d1e6677b","added_by":"auto","created_at":"2025-07-31 10:43:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1193571,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7091849/v1/5836543a-412c-491b-b9fd-92df69c7f2e9.pdf"},{"id":88002497,"identity":"b9ace63d-d787-4e0a-b654-b219cae0f551","added_by":"auto","created_at":"2025-07-31 10:27:39","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":243493,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFileQolintargetedtherapytrialsDL.docx","url":"https://assets-eu.researchsquare.com/files/rs-7091849/v1/bd442ce7651d4e43a4f352f9.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Reporting of Health-Related Quality of Life Outcome Measures in Genotype based Targeted Therapies for Advanced Cancers","fulltext":[{"header":"1. BACKGROUND","content":"\u003cp\u003eMatched targeted therapies (MTTs) have become a cornerstone of personalised cancer treatment, particularly for patients with advanced or refractory malignancies (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). These therapies, which are selected based on tumour-specific genetic or molecular alterations, have demonstrated improved progression free survival either as monotherapy or in combination with standard systemic anticancer treatments, however there is limited improvement in overall survival (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). A recent Cochrane meta-analysis highlighted the lack of evidence on the impact of MTTs on quality of life in patients with advanced cancers (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). This gap is concerning, patient reported outcomes (PROs) such as health related quality of life (HRQoL) are increasingly recognized as a critical outcome in oncology, particularly in non-curative settings where prolongation of life may be modest, and the interventions that improve physical and psychological wellbeing may be of more important (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHealth-related quality of life are questionnaires completed by patients that encompasses multiple domains of patient perspective on his/her health. The domains in these questionnaires frequently include physical functioning, emotional health, symptom burden, and social participation\u0026mdash;and provides insight into how a treatment affects patients beyond traditional clinical safety and efficacy. HRQOL can play a pivotal role in shared treatment decision-making and are increasingly recognized as critical outcomes for guiding clinical recommendations and shaping health policy (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Despite this, HRQoL assessments are inconsistently implemented and reported in clinical trials (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). In some cases, they are omitted entirely, particularly when treatments are anticipated to have higher adverse events (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). This selective and inconsistent reporting raises concerns about bias and underscores the need for standardized, transparent, and patient-centered reporting practices (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo improve the quality and transparency of HRQoL reporting, the CONSORT-PRO (Consolidated Standards of Reporting Trials\u0026ndash;Patient-Reported Outcomes) extension was introduced in 2013 (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The guideline outlined a set of recommendations designed to ensure the completeness, consistency, and interpretability of patient-reported outcome data in randomized trials (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Despite this, HRQoL data collection is still inconsistently reported (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). In addition, variability in measurement tools, and delays in publication of patient-reported outcomes further limit the interpretability and clinical relevance of HRQoL outcomes (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). In this study, we aim to systematically review these concerns in targeted therapy trials for pretreated metastatic or relapsed cancer by evaluating their inclusion, reporting, and quality of HRQoL data.\u003c/p\u003e"},{"header":"2. METHODS","content":"\u003cp\u003e\u003cb\u003eEligibility criteria and Literature search\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe conducted a comprehensive search in three databases namely CENTRAL, EMBASE and MEDLINE without language restrictions until 30th October 2024 (Supplementary 1). Additionally, we checked reference lists of included studies, previous systematic reviews, and studies citing eligible articles. The 'related articles' feature in PubMed was also utilized. Furthermore, conference reports from the past five years were sourced from the following meetings: European Haematology Association, American Society of Haematology, European Society of Medical Oncology (ESMO), American Society of Clinical Oncology (ASCO) and British Cancer Research Meeting.\u003c/p\u003e\u003cp\u003eStudies comparing MTT alone or in combination with standard-of-care treatment, either chemotherapy or hormonal therapy, were considered. Only randomized controlled trials were included. Studies comparing MTT with immunotherapy or immune modulators were excluded to maintain consistency with our previously published systematic review (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eSelection of studies\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTitles and abstracts retrieved from the database searches were screened in duplicate. Studies selected for full-text screening were also assessed in duplicate. Disagreements were resolved through consensus.\u003c/p\u003e\u003cp\u003eIn instances where HRQoL results were not reported in the primary publication, a secondary search was conducted to identify companion publications reporting HRQoL data. These secondary publications were identified via PubMed and google using the name of the drug, the trial registration number and trial acronym.\u003c/p\u003e\u003cp\u003e\u003cb\u003eData Extraction\u003c/b\u003e\u003c/p\u003e\u003cp\u003eData was extracted by a study author (TF) and rechecked by a second a second author (NS). Any discrepancy identified in the extraction was resolved by consensus. For each included RCT, data were extracted from the primary and secondary publications, associated supplementary materials, and the ClinicalTrials.gov registry. Extracted trial characteristics included: first author, study acronym, year of publication, digital object identifier (DOI), journal name, type of therapy and intervention, tumour type, primary endpoint, trial design (classified as superiority or non-inferiority), blinding (blinded or open-label), comparator type (placebo or other), trial outcome (classified as positive or negative based on the statistical significance of the primary endpoint), funding source (pharmaceutical industry sponsored vs. non-profit or academic), and geographical scope (single-country or multi-country trial conduct).\u003c/p\u003e\u003cp\u003eTo assess the reporting of HRQoL outcomes, main manuscripts and study protocols/trial registry records were reviewed to determine whether HRQoL was included as a trial endpoint. For each publication that included HRQoL as their endpoints, the following additional information was extracted: whether HRQoL data was reported in the primary or secondary publication, the time elapsed between primary and secondary publication (in days and months), the type of assessment tools used and reported compliance with HRQoL questionnaires.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStatistical analysis and Adherence to CONSORT PRO checklist\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAll statistical analyses were conducted using R version 4.1.2 (R Foundation for Statistical Computing, Vienna, Austria). Differences in the reporting of health-related quality of life (HRQoL) as a primary, secondary, or exploratory endpoint were examined. The reporting of HRQoL in primary and subsequent trial publications was also assessed. Kaplan\u0026ndash;Meier survival curves were generated to estimate the time to HRQoL data publication. For trials published from 2013 onwards, adherence to the CONSORT-PRO extension for reporting patient-reported outcomes (PROs) was evaluated using selected checklist items, as outlined at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.consort-statement.org/extensions\u003c/span\u003e\u003cspan address=\"http://www.consort-statement.org/extensions\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e"},{"header":"3. RESULTS","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Study selection\u003c/h2\u003e\n \u003cp\u003eA total of 208 full-text articles were screened for full-text assessment. Of these, 147 studies were excluded for reasons: absence of a comparator arm (n\u0026thinsp;=\u0026thinsp;46), use of the wrong line of treatment (n\u0026thinsp;=\u0026thinsp;28), inappropriate study design (n\u0026thinsp;=\u0026thinsp;18), retrospective cohort design (n\u0026thinsp;=\u0026thinsp;15), wrong intervention (n\u0026thinsp;=\u0026thinsp;8), wrong patient population (n\u0026thinsp;=\u0026thinsp;7), ongoing trial status (n\u0026thinsp;=\u0026thinsp;7), wrong setting (n\u0026thinsp;=\u0026thinsp;5), wrong outcomes (n\u0026thinsp;=\u0026thinsp;4), wrong comparator (n\u0026thinsp;=\u0026thinsp;4), prospective cohort study design (n\u0026thinsp;=\u0026thinsp;4), or lack of full publication of data (n\u0026thinsp;=\u0026thinsp;1). This resulted in a final inclusion of 61 randomized controlled trials (RCTs) for this analysis. The study selection process is summarized in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Study characteristics\u003c/h2\u003e\n \u003cp\u003eA total of 61 eligible RCTs (\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e72\u003c/span\u003e) were published between 2008 and 2024. Of these, 25 (41%) trials were published after 2020, followed by 31 (51%) trials published between 2011\u0026ndash;2020. Based on tumour sites, 22 (36%) trials were related to breast and prostate cancer studies, followed by 14 (23%) studies in lung and gynaecological cancers. Detailed study characteristics can be found in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Primary Endpoints and Inclusion of HRQoL in Trial Designs\u003c/h2\u003e\n \u003cp\u003eProgression-free survival (PFS) and overall survival (OS) were the most reported primary endpoints, included in 44 (72%) and 9 (14%) studies respectively (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Overall response rate (ORR) and other endpoints were reported in 5 (8%) and 3 (5%) trials respectively. Notably, none of the 61 trials included HRQoL as a primary endpoint. HRQoL was included as a secondary endpoint in 26 trials (43%) and as an exploratory endpoint in 9 trials (15%), while it was not evaluated in 26 trials (43%) (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Among the 49 positive trials, HRQoL was not assessed in 19 (39%), whereas among the 12 negative trials, 7 (58%) did not include HRQoL assessment. HRQoL was more frequently evaluated in certain tumour types, such as gynaecological cancers (86%) and lung cancer (57%). Only half of breast cancer trials reported HRQoL endpoints.\u003c/p\u003e\n \u003cp\u003eAmong the 35 trials that included HRQoL as a secondary or exploratory endpoint, many employed more than one assessment instrument. Therefore, the total number of tool usages exceeds the number of trials. The most frequently used instrument was the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ), which appeared in 20 instances. This was followed by the Functional Assessment of Cancer Therapy (FACT) family of tools (n\u0026thinsp;=\u0026thinsp;14) and the EQ-5D-5L (n\u0026thinsp;=\u0026thinsp;10). Other tools included the Brief Pain Inventory (BPI; n\u0026thinsp;=\u0026thinsp;5) and a small number of trial-specific or less commonly used instruments. A detailed description of HRQoL inclusion by trial characteristics is reported in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1. Study Characteristics and HRQoL Inclusion as Secondary or Exploratory Endpoints.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cimg 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\" width=\"497\" height=\"718\"\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cimg width=\"11\" height=\"13\" src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAUBAMAAAB2TKBEAAAAAXNSR0IArs4c6QAAACpQTFRFAAAAAABmADo6ADqQAGa2OgAAOjoAOjo6Zrb/tmYAtv//25A62////9uQgEJowQAAAAF0Uk5TAEDm2GYAAAAJcEhZcwAAFiUAABYlAUlSJPAAAAAZdEVYdFNvZnR3YXJlAE1pY3Jvc29mdCBPZmZpY2V/7TVxAAAAJklEQVQYV2NgIAlw2kCVczugMa6WqUdAhIBS3FLoDLgU8WpwOgwA5/kFkorfLysAAAAASUVORK5CYII=\" alt=\"image\"\u003eOther Cancers Head and Neck, Upper GI, Skin, Bladder.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAbbreviations: ORR: objective response rate, OS: overall survival, PFS: progression free survival, EORTC QLQ: European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire, FACT: Functional Assessment of Cancer Therapy, EQ-5D-5L: EuroQol 5-Dimension 5-Level Questionnaire, BPI: brief pain inventory, NFOSI: NCCN\u0026ndash;Functional Assessment of Cancer Therapy Ovarian Symptom Index, PGI: patient global impression, TOI: trial outcome index\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4 Reporting of HRQoL Results in Primary Publications\u003c/h2\u003e\n \u003cp\u003eWe assessed whether HRQoL results were reported in the primary publication. Among the 61 included RCTs, only 17 (28%) reported HRQoL outcomes in their main manuscript, while the remaining 44 (72%) did not (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). A notable trend emerged over time, with HRQoL reporting becoming less common in more recent trials. Among studies published after 2020, only 2 out of 25 (8%) reported HRQoL results in the primary publication, compared to 11 out of 23 (48%) for trials published between 2016 and 2020. Regarding trial results, HRQoL outcomes were reported in 16 out of 49 positive trials (33%) and only 1 out of 12 negative trials (8%). When examined by tumour type, HRQoL reporting was most frequent in trials on lung cancer (57%). Finally, among the 9 trials with missing data on HRQoL compliance rates, 7 (66.7%) reported HRQoL in the primary publication, while 2 (33.3%) did not. A complete breakdown of HRQoL reporting across study characteristics is presented in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2. Study Characteristics and Inclusion of HRQoL in Primary Publication\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cimg 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\" width=\"442\" height=\"615\"\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cimg width=\"11\" height=\"13\" src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAUBAMAAAB2TKBEAAAAAXNSR0IArs4c6QAAACpQTFRFAAAAAABmADo6ADqQAGa2OgAAOjoAOjo6Zrb/tmYAtv//25A62////9uQgEJowQAAAAF0Uk5TAEDm2GYAAAAJcEhZcwAAFiUAABYlAUlSJPAAAAAZdEVYdFNvZnR3YXJlAE1pY3Jvc29mdCBPZmZpY2V/7TVxAAAAJklEQVQYV2NgIAlw2kCVczugMa6WqUdAhIBS3FLoDLgU8WpwOgwA5/kFkorfLysAAAAASUVORK5CYII=\" alt=\"image\"\u003eOther Cancers Head and Neck, Upper GI, Skin, Bladder. \u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e ORR: objective response rate, OS: overall survival, PFS: progression free survival\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e3.5 Compliance with CONSORT PRO reporting standards\u003c/h2\u003e\n \u003cp\u003eAmong the trials that reported their HRQoL results, we evaluated compliance with selected items from the CONSORT-PRO extension checklist among trials that reported HRQoL in either the primary or a secondary publication and were published from 2013 onward. A total of 26 trials met these criteria and were included in this analysis. Identification of the patient-reported outcome (PRO) as a primary or secondary endpoint in the abstract was fulfilled in only 6 trials (23%). None of the trials stated a PRO hypothesis or identified the relevant domains of interest, nor did any provide scientific background or rationale for PRO assessment. Information on the validity and reliability of the HRQoL instruments used was provided or cited in 19 trials (73%), representing the most consistently reported item. In contrast, statistical methods for handling missing PRO data were described in only 3 trials (12%). Transparency regarding the number of PRO outcome data at baseline and subsequent time points was reported in 17 trials (65.4%). Similarly, 17 trials (65.4%) presented results for each group along with estimated effect sizes and their precision. Fifteen trials (57.7%) included a table of baseline demographic and clinical characteristics. Only 2 trials (8%) discussed PRO-specific limitations or the implications of HRQoL findings for generalisability or clinical practice. No trials provided an interpretation that balanced benefits and harms while considering other relevant evidence. Full results of the CONSORT-PRO compliance analysis are presented in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e and Supplementary Table 1.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCONSORT-PRO Checklist Compliance Among Trials Reporting HRQoL\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eChecklist items\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRCTs reporting QoL in primary, secondary publication or both from 2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1b: The PRO should be identified in the abstract as a primary or secondary outcome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2a CONSORT 2010: Scientific background and explanation of rationale.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2b: The PRO hypothesis should be stated, and relevant domains identified, if applicable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6a: Evidence of PRO instrument validity and reliability should be provided or cited\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12a: Statistical approaches for dealing with missing data are explicitly stated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13a CONSORT 2010: For each group, the numbers of participants who were randomly assigned, received intended treatment, and were analyzed for the primary outcome.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 CONSORT 2010: A table showing baseline demographic and clinical characteristics for each group.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17a CONSORT 2010: For each primary and secondary outcome, results for each group, and the estimated effect size and its precision (such as 95% confidence interval).\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20/21: PRO-specific limitations and implications for generalizability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 CONSORT 2010: Interpretation consistent with results, balancing benefits and harms, and considering other relevant evidence.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e*17 RCTs reported HRQoL data in their primary publication, 9 RCTs reported HRQoL data in their secondary publications\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eHealth-related quality of life remains under-prioritised and inconsistently reported in randomised controlled trials of matched targeted therapies for pretreated advanced cancers. Our findings are consistent with those of similar studies conducted in other cancer settings (Supplementary table 2). Despite the increasing use of biomarker-driven therapies in non-curative cancer settings, none of the 61 trials included HRQoL as a primary endpoint, and fewer than one in three reported HRQoL in the main publication. This is concerning, as the population under study often experiences marginal survival benefit, making patient-reported outcomes such as HRQoL especially vital for shared decision-making and patient-centred care (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e). Our findings are consistent with similar studies, which have shown that improvements in PFS are poorly correlated with overall quality of life and do not reliably predict HRQoL benefit (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Importantly, we found that trials showing PFS gains without HRQoL improvement often framed outcomes positively (e.g., \"HRQoL maintained\"), suggesting the presence of reporting bias (Supplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; (\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan additionalcitationids=\"CR74 CR75 CR76 CR77 CR78\" citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e)). Furthermore, our CONSORT-PRO compliance analysis found no trials stating a prior HRQoL hypotheses, and few that described handling of missing data\u0026mdash;both critical elements for methodological robustness (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Supplementary Table\u0026nbsp;1). This further validates a consistent theme that most phase 3 trials fail to adjust HRQoL outcomes for baseline scores, introducing potential bias and reducing analytic validity (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOne particularly important insight from our review is the disparity in HRQoL reporting based on trial outcome. Trials with negative or non-significant results were significantly less likely to publish HRQoL data or do so in a timely fashion (Supplementary Figs.\u0026nbsp;1 and 2). These reporting delays critically hampers the ability of clinicians and policymakers to make informed evaluations about therapeutic value of MTTs, where toxicities may be chronic and insidious, and quality of life\u0026mdash;not just tumour control\u0026mdash;should drive clinical decision-making. For example, in a meta-analysis of 791 phase 3 oncology trials, they found that although 61% collected patient reported outcomes, only 34% published global HRQoL outcomes, and just 11% demonstrated global HRQoL superiority (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). It is also worth highlighting that HRQoL deterioration is more commonly associated with targeted agents than traditionally perceived (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e). Samuel et al. noted that inferior HRQoL was more frequently observed with MTTs than with cytotoxic chemotherapy, challenging the assumption that \"targeted\" equates to \"better tolerated\" (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Our own review supports this, with multiple trials using MTTs reporting PRO data that, when available, revealed significant symptom burden, yet without the necessary methodological clarity to interpret the data effectively.\u003c/p\u003e\u003cp\u003eThe strength of this study is that it specifically focusses on HRQoL outcomes in genotype based MTT trials for previously treated advanced cancer patients providing a better understanding the impact of MTT in this setting. However, there exist several limitations. First, despite a comprehensive search strategy, some eligible trials may have been missed. Second although we focused on published data, delayed or unpublished HRQoL results\u0026mdash;particularly in negative trials\u0026mdash;may have led to underestimation of the true reporting gap. Finally, the modest number of trials relative to broader reviews limits generalisability but enhances the specificity to MTTs, where these gaps are particularly concerning.\u003c/p\u003e"},{"header":"5. CONCLUSIONS","content":"\u003cp\u003eIn conclusion, the consistent under-reporting, delayed publication, and poor methodological quality of HRQoL data in MTT trials represents a major disconnect between precision oncology and patient-centred care. The emphasis on alternative endpoints such as PFS has overshadowed meaningful outcomes such as overall survival and quality of life. Therefore, Incorporating HRQoL as a core outcome from the outset of trial design\u0026mdash;and reporting it transparently regardless of outcome\u0026mdash;must become standard practice. Doing so will ensure treatments are evaluated not only by how long patients live, but also by how well they live.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eMTT: Matched targeted therapy\u003c/p\u003e\n\u003cp\u003eSOC: Standard-of-care\u003c/p\u003e\n\u003cp\u003eHRQoL: Health-related quality of life\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eORR: Objective response rate\u003c/p\u003e\n\u003cp\u003eOS: Overall survival\u003c/p\u003e\n\u003cp\u003ePFS: Progression free survival\u003c/p\u003e\n\u003cp\u003eEORTC QLQ: European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire\u003c/p\u003e\n\u003cp\u003eFACT: Functional Assessment of Cancer Therapy\u003c/p\u003e\n\u003cp\u003eEQ-5D-5L: EuroQol 5-Dimension 5-Level Questionnaire\u003c/p\u003e\n\u003cp\u003eBPI: brief pain inventory\u003c/p\u003e\n\u003cp\u003eNFOSI: NCCN\u0026ndash;Functional Assessment of Cancer Therapy Ovarian Symptom Index\u003c/p\u003e\n\u003cp\u003ePGI: patient global impression\u003c/p\u003e\n\u003cp\u003eTOI: trial outcome index\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e: All data generated or analysed during this study are included in this published article [and its supplementary information files].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest:\u0026nbsp;\u003c/strong\u003eAuthors declare no competing interest in preparing this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003eConceptualization, methodology, formal analysis and investigation and writing original draft preparation: TF,\u003csup\u003e\u0026nbsp;\u003c/sup\u003eFK, NS; Supervision: NS; Writing - review and editing: CB, SRM, PD, RK. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eNo funding was received in preparing this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMin HY, Lee HY. Molecular targeted therapy for anticancer treatment. Exp Mol Med. 2022;54(10):1670-94.\u003c/li\u003e\n\u003cli\u003eKazmi F, Shrestha N, Liu TFD, Foord T, Heesen P, Booth S, et al. Next-generation sequencing for guiding matched targeted therapies in people with relapsed or metastatic cancer. Cochrane Database Syst Rev. 2025;3(3):CD014872.\u003c/li\u003e\n\u003cli\u003eYang TK, Yu YF, Tsai CL, Li HJ, Yang PS, Huang KW, Cheng JC. 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Nat Rev Clin Oncol. 2016;13(5):319-25.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"health-and-quality-of-life-outcomes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hqlo","sideBox":"Learn more about [Health and Quality of Life Outcomes](http://hqlo.biomedcentral.com)","snPcode":"12955","submissionUrl":"https://submission.nature.com/new-submission/12955/3","title":"Health and Quality of Life Outcomes","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Quality of life, matched targeted therapies, advanced cancer","lastPublishedDoi":"10.21203/rs.3.rs-7091849/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7091849/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eGenotype based matched targeted therapies (MTT) trials have shown clinical benefit in patients with advanced cancer however health-related quality of life (HRQoL) outcomes are often inconsistently reported in these trials. In this study, we evaluated the overall reporting and quality of HRQoL based randomised controlled trials (RCTs).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe searched various biomedical databases (CENTRAL, MEDLINE, EMBASE) from 2000 to 2024, for eligible RCTs evaluating biomarker based MTTs (alone or combined with standard of care systemic standard-of-care [SOC]) versus SOC or placebo in patients with advanced cancers that had progressed after at least one prior systemic therapy. We evaluated inclusion of HRQoL endpoints, timing of reporting, tools used, and adherence to selected CONSORT-PRO guidelines.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eA total of 208 studies were assessed for eligibility. No studies reported HRQoL as a primary endpoint. Among 61 RCTs (n\u0026thinsp;=\u0026thinsp;21,103), HRQoL was included as a secondary or exploratory endpoint in 35 (57.4%) trials. Only 17 (27.9%) trials reported HRQoL in the primary publication. Inclusion and reporting declined over time, with only 44.0% of trials after 2020 including HRQoL and just 8.0% reporting it in the primary publication. Trials with positive primary outcomes reported HRQoL more frequently and earlier. Compliance with CONSORT-PRO was poor: no trial stated HRQoL in their hypothesis or described handling of missing data. Common instruments included EORTC QLQ (n\u0026thinsp;=\u0026thinsp;20), FACT (n\u0026thinsp;=\u0026thinsp;14), and EQ-5D (n\u0026thinsp;=\u0026thinsp;10).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eHRQoL is significantly under-reported in MTT based trials, with declining inclusion and poor adherence to reporting standards. This is particularly important as MTT do not significantly improve overall survival in this cohort and therefore quality of life becomes paramount for these patients.\u003c/p\u003e","manuscriptTitle":"Reporting of Health-Related Quality of Life Outcome Measures in Genotype based Targeted Therapies for Advanced Cancers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-31 10:19:34","doi":"10.21203/rs.3.rs-7091849/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-13T04:14:36+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-07T12:14:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-07T10:48:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"198865472102874796817874155590982400746","date":"2025-11-09T17:30:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"79754094423017928094684930201434292376","date":"2025-11-08T20:57:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"80890781640854964768122344750508713365","date":"2025-08-23T07:42:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-22T19:56:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"295370527887896810744794906454463662168","date":"2025-08-21T17:20:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-28T07:01:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-14T03:59:05+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-14T03:58:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Health and Quality of Life Outcomes","date":"2025-07-10T10:11:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"health-and-quality-of-life-outcomes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hqlo","sideBox":"Learn more about [Health and Quality of Life Outcomes](http://hqlo.biomedcentral.com)","snPcode":"12955","submissionUrl":"https://submission.nature.com/new-submission/12955/3","title":"Health and Quality of Life Outcomes","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3f0eeaf4-a8a5-49a0-8d3f-ffb2d890938f","owner":[],"postedDate":"July 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-23T01:08:40+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-31 10:19:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7091849","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7091849","identity":"rs-7091849","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}