NorthWest Biotherapeutics Inc (NWBO)

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The median for the controls in all five comparator trials are very closely centered between 15 and 17 with an average of 16.5 months.

And you can see from the slide presented below here (at NYAS), that the footnote (1) below the chart indicates that the data was based on "reconstructed individual patient data (IPD)”. Now, as you point out, the ECA does not have “patient level data” which would allow for a one-by-one patient match; however, the DCVax-L external control arm instead used a “matching-adjusted indirect comparison” (MAIC) which comes very, very close to a one-to-one. So instead of matching the patients one-to-one, it matches by percentage each prognostic factor.



One can also see from the article passage cited below that when patients are combined from multiple randomized control trials, it improves the unanchored status when using a propensity scoring tool like the MAIC.
https://www.sciencedirect.com/science/article/pii/S1098301521001492

When there is no direct comparison of products conducted within RCTs, multiple RCTs can be combined, and ‘anchored’ indirect treatment comparisons can be made using network meta-analysis methods.13 When RCTs are not available, methods for ‘unanchored’ meta-analysis can still be used, such as matching-adjusted indirect comparisons (MAIC) and simulated treatment comparisons (STC).14, 15, 16 When patient level data is available, more direct comparison methods can be applied such as propensity score matching or Bayesian methods to help reduce selection bias and differences between comparator cohorts.17, 18, 19 Some formal HTA guidance is available on these approaches, and their limitations from National Institute for Health and Care Excellence’s (NICE) decision support unit.20,21 In general, unanchored comparisons are less well established than anchored methods, and additional care is needed on interpretation.12,22,23

So again... using propensity scoring like the MAIC will give the DCVax-L ECA that "additional care."
(Note: HTA = Health Technology Assessment)

Additionally,

External comparator (EC) data (also referred to as “external controls,” “historical comparators,” or “synthetic controls”) collected from patient cohorts outside of the clinical study, or “index study” is being used more frequently to provide contextual information on a product’s clinical efficacy, safety, and cost-effectiveness. Here patient selection criteria from the index study protocol are applied to the external data source (to the extent possible) so that the comparator population looks as similar as possible to the index study population.12,24 This type of supplementary dataset can be used for naive (unadjusted comparison) or adjusted indirect treatment comparison using STC or MAIC approaches.

I would bet that the journal article will very likely cover in great detail, both in its body and its supplemental material, the approach that was used to assemble the ECA for both DCVax-L trials (newly diagnosed and recurrent).

Therefore, using the MAIC assists in moving the "unanchored" patient data towards more of an "anchored" patient level data status.