Impact of the COVID-19 Pandemic on a Cancer Fast-Track Programme.

INTRODUCTION: The COVID-19 pandemic has disrupted many aspects of clinical practice in oncology, particularly regarding early cancer diagnosis, sparking public health concerns that possible delays could increase the proportion of patients diagnosed at advanced stages. In 2009, a cancer fast-track program (CFP) was implemented at the Clinico-Malvarrosa Health Department in Valencia, Spain with the aim of shortening waiting times between suspected cancer symptoms, diagnosis and therapy initiation. OBJECTIVES: The study aimed to explore the effects of the COVID-19 pandemic on our cancer diagnosis fast-track program. METHODS: The program workflow (patients included and time periods) was analysed from the beginning of the state of alarm on March 16th, 2020 until March 15th, 2021. Data was compared with data from the same period of time from the year before (2019). RESULTS: During the pandemic year, 975 suspected cancer cases were submitted to the CFP. The number of submissions only decreased during times of highest COVID-19 incidence and stricter lockdown, and overall, referrals were slightly higher than in the previous 2 years. Cancer diagnosis was confirmed in 197 (24.1%) cases, among which 33% were urological, 23% breast, 16% gastrointestinal and 9% lung cancer. The median time from referral to specialist appointment was 13 days and diagnosis was reached at a median of 18 days. In confirmed cancer cases, treatment was started at around 30 days from time of diagnosis. In total, 61% of cancer disease was detected at early stage, 20% at locally advanced stage, and 19% at advanced stage, displaying time frames and case proportions similar to pre-pandemic years. CONCLUSIONS: Our program has been able to maintain normal flow and efficacy despite the challenges of the current pandemic, and has proven a reliable tool to help primary care physicians referring suspected cancer patients.

Ten-year assessment of a cancer fast-track programme to connect primary care with oncology: reducing time from initial symptoms to diagnosis and treatment initiation.

BACKGROUND: Cancer is the second leading cause of mortality worldwide. Integrating different levels of care by implementing screening programmes, extending diagnostic tools and applying therapeutic advances may increase survival. We implemented a cancer fast-track programme (CFP) to shorten the time between suspected cancer symptoms, diagnosis and therapy initiation. PATIENTS AND METHODS: Descriptive data were collected from the 10 years since the CFP was implemented (2009-2019) at the Clinico-Malvarrosa Health Department in Valencia, Spain. General practitioners (GPs), an oncology coordinator and 11 specialists designed guidelines for GP patient referral to the CFP, including criteria for breast, digestive, gynaecological, lung, urological, dermatological, head and neck, and soft tissue cancers. Patients with enlarged lymph nodes and constitutional symptoms were also considered. On identifying patients with suspected cancer, GPs sent a case proposal to the oncology coordinator. If criteria were met, an appointment was quickly made with the patient. We analysed the timeline of each stage of the process. RESULTS: A total of 4493 suspected cancer cases were submitted to the CFP, of whom 4019 were seen by the corresponding specialist. Cancer was confirmed in 1098 (27.3%) patients: breast cancer in 33%, urological cancers in 22%, gastrointestinal cancer in 19% and lung cancer in 15%. The median time from submission to cancer testing was 11 days, and diagnosis was reached in a median of 19 days. Treatment was started at a median of 34 days from diagnosis. CONCLUSIONS: The findings of this study show that the interval from GP patient referral to specialist testing, cancer diagnosis and start of therapy can be reduced. Implementation of the CFP enabled most patients to begin curative intended treatment, and required only minimal resources in our setting.

Combination of phenotype and polygenic risk score in breast cancer risk evaluation in the Spanish population: a case -control study.

BACKGROUND: In recent years, the identification of genetic and phenotypic biomarkers of cancer for prevention, early diagnosis and patient stratification has been a main objective of research in the field. Different multivariable models that use biomarkers have been proposed for the evaluation of individual risk of developing breast cancer. METHODS: This is a case control study based on a population-based cohort. We describe and evaluate a multivariable model that incorporates 92 Single-nucleotide polymorphisms (SNPs) (Supplementary Table S1) and five different phenotypic variables and which was employed in a Spanish population of 642 healthy women and 455 breast cancer patients. RESULTS: Our model allowed us to stratify two groups: high and low risk of developing breast cancer. The 9th decile included 1% of controls vs 9% of cases, with an odds ratio (OR) of 12.9 and a p-value of 3.43E-07. The first decile presented an inverse proportion: 1% of cases and 9% of controls, with an OR of 0.097 and a p-value of 1.86E-08. CONCLUSIONS: These results indicate the capacity of our multivariable model to stratify women according to their risk of developing breast cancer. The major limitation of our analysis is the small cohort size. However, despite the limitations, the results of our analysis provide proof of concept in a poorly studied population, and opens up the possibility of using this method in the routine screening of the Spanish population.